---
_id: '63611'
abstract:
- lang: eng
text: When humans interact with artificial intelligence (AI), one desideratum is
appropriate trust. Typically, appropriate trust encompasses that humans trust
AI except for instances in which they either explicitly notice AI errors or are
suspicious that errors could be present. So far, appropriate trust or related
notions have mainly been investigated by assessing trust and reliance. In this
contribution, we argue that these assessments are insufficient to measure the
complex aim of appropriate trust and the related notion of healthy distrust. We
introduce and test the perspective of covert visual attention as an additional
indicator for appropriate trust and draw conceptual connections to the notion
of healthy distrust. To test the validity of our conceptualization, we formalize
visual attention using the Theory of Visual Attention and measure its properties
that are potentially relevant to appropriate trust and healthy distrust in an
image classification task. Based on temporal-order judgment performance, we estimate
participants' attentional capacity and attentional weight toward correct and incorrect
mock-up AI classifications. We observe that misclassifications reduce attentional
capacity compared to correct classifications. However, our results do not indicate
that this reduction is beneficial for a subsequent judgment of the classifications.
The attentional weighting is not affected by the classifications' correctness
but by the difficulty of categorizing the stimuli themselves. We discuss these
results, their implications, and the limited potential for using visual attention
as an indicator of appropriate trust and healthy distrust.
article_number: '1694367'
article_type: original
author:
- first_name: Tobias Martin
full_name: Peters, Tobias Martin
id: '92810'
last_name: Peters
orcid: 0009-0008-5193-6243
- first_name: Kai
full_name: Biermeier, Kai
id: '55908'
last_name: Biermeier
orcid: 0000-0002-2879-2359
- first_name: Ingrid
full_name: Scharlau, Ingrid
id: '451'
last_name: Scharlau
orcid: 0000-0003-2364-9489
citation:
ama: 'Peters TM, Biermeier K, Scharlau I. Assessing healthy distrust in human-AI
interaction: interpreting changes in visual attention. Frontiers in Psychology.
2026;16. doi:10.3389/fpsyg.2025.1694367'
apa: 'Peters, T. M., Biermeier, K., & Scharlau, I. (2026). Assessing healthy
distrust in human-AI interaction: interpreting changes in visual attention. Frontiers
in Psychology, 16, Article 1694367. https://doi.org/10.3389/fpsyg.2025.1694367'
bibtex: '@article{Peters_Biermeier_Scharlau_2026, title={Assessing healthy distrust
in human-AI interaction: interpreting changes in visual attention}, volume={16},
DOI={10.3389/fpsyg.2025.1694367},
number={1694367}, journal={Frontiers in Psychology}, publisher={Frontiers Media
SA}, author={Peters, Tobias Martin and Biermeier, Kai and Scharlau, Ingrid}, year={2026}
}'
chicago: 'Peters, Tobias Martin, Kai Biermeier, and Ingrid Scharlau. “Assessing
Healthy Distrust in Human-AI Interaction: Interpreting Changes in Visual Attention.”
Frontiers in Psychology 16 (2026). https://doi.org/10.3389/fpsyg.2025.1694367.'
ieee: 'T. M. Peters, K. Biermeier, and I. Scharlau, “Assessing healthy distrust
in human-AI interaction: interpreting changes in visual attention,” Frontiers
in Psychology, vol. 16, Art. no. 1694367, 2026, doi: 10.3389/fpsyg.2025.1694367.'
mla: 'Peters, Tobias Martin, et al. “Assessing Healthy Distrust in Human-AI Interaction:
Interpreting Changes in Visual Attention.” Frontiers in Psychology, vol.
16, 1694367, Frontiers Media SA, 2026, doi:10.3389/fpsyg.2025.1694367.'
short: T.M. Peters, K. Biermeier, I. Scharlau, Frontiers in Psychology 16 (2026).
date_created: 2026-01-14T14:21:59Z
date_updated: 2026-01-14T14:29:03Z
department:
- _id: '424'
- _id: '660'
doi: 10.3389/fpsyg.2025.1694367
intvolume: ' 16'
keyword:
- appropriate trust
- healthy distrust
- visual attention
- Theory of Visual Attention
- human-AI interaction
- Bayesian cognitive model
- image classification
language:
- iso: eng
project:
- _id: '124'
name: 'TRR 318 ; TP C01: Gesundes Misstrauen in Erklärungen'
publication: Frontiers in Psychology
publication_identifier:
issn:
- 1664-1078
publication_status: published
publisher: Frontiers Media SA
status: public
title: 'Assessing healthy distrust in human-AI interaction: interpreting changes in
visual attention'
type: journal_article
user_id: '92810'
volume: 16
year: '2026'
...
---
_id: '59755'
abstract:
- lang: eng
text: "Due to the application of Artificial Intelligence (AI) in high-risk domains
like law or medicine,\r\ntrustworthy AI and trust in AI are of increasing scientific
and public relevance. A typical conception,\r\nfor example in the context of medical
diagnosis, is that a knowledgeable user receives AIgenerated\r\nclassification
as advice. Research to improve such interactions often aims to foster the\r\nuser’s
trust, which in turn should improve the combined human-AI performance. Given that
AI\r\nmodels can err, we argue that the possibility to critically review, thus
to distrust, an AI decision is\r\nan equally interesting target of research.\r\nWe
created two image classification scenarios in which the participants received
mock-up\r\nAI advice. The quality of the advice decreases for a phase of the experiment.
We studied the\r\ntask performance, trust and distrust of the participants, and
tested whether an instruction to\r\nremain skeptical and review each piece of
advice led to a better performance compared to a\r\nneutral condition. Our results
indicate that this instruction does not improve but rather worsens\r\nthe participants’
performance. Repeated single-item self-report of trust and distrust shows an\r\nincrease
in trust and a decrease in distrust after the drop in the AI’s classification
quality, with no\r\ndifference between the two instructions. Furthermore, via
a Bayesian Signal Detection Theory\r\nanalysis, we provide a procedure to assess
appropriate reliance in detail, by quantifying whether\r\nthe problems of under-
and over-reliance have been mitigated. We discuss implications of our\r\nresults
for the usage of disclaimers before interacting with AI, as prominently used in
current\r\nLLM-based chatbots, and for trust and distrust research."
article_type: original
author:
- first_name: Tobias Martin
full_name: Peters, Tobias Martin
id: '92810'
last_name: Peters
orcid: 0009-0008-5193-6243
- first_name: Ingrid
full_name: Scharlau, Ingrid
id: '451'
last_name: Scharlau
orcid: 0000-0003-2364-9489
citation:
ama: 'Peters TM, Scharlau I. Interacting with fallible AI: Is distrust helpful when
receiving AI misclassifications? Frontiers in Psychology. 2025;16. doi:10.3389/fpsyg.2025.1574809'
apa: 'Peters, T. M., & Scharlau, I. (2025). Interacting with fallible AI: Is
distrust helpful when receiving AI misclassifications? Frontiers in Psychology,
16. https://doi.org/10.3389/fpsyg.2025.1574809'
bibtex: '@article{Peters_Scharlau_2025, title={Interacting with fallible AI: Is
distrust helpful when receiving AI misclassifications?}, volume={16}, DOI={10.3389/fpsyg.2025.1574809},
journal={Frontiers in Psychology}, author={Peters, Tobias Martin and Scharlau,
Ingrid}, year={2025} }'
chicago: 'Peters, Tobias Martin, and Ingrid Scharlau. “Interacting with Fallible
AI: Is Distrust Helpful When Receiving AI Misclassifications?” Frontiers in
Psychology 16 (2025). https://doi.org/10.3389/fpsyg.2025.1574809.'
ieee: 'T. M. Peters and I. Scharlau, “Interacting with fallible AI: Is distrust
helpful when receiving AI misclassifications?,” Frontiers in Psychology,
vol. 16, 2025, doi: 10.3389/fpsyg.2025.1574809.'
mla: 'Peters, Tobias Martin, and Ingrid Scharlau. “Interacting with Fallible AI:
Is Distrust Helpful When Receiving AI Misclassifications?” Frontiers in Psychology,
vol. 16, 2025, doi:10.3389/fpsyg.2025.1574809.'
short: T.M. Peters, I. Scharlau, Frontiers in Psychology 16 (2025).
date_created: 2025-05-02T09:22:39Z
date_updated: 2025-05-27T09:10:09Z
department:
- _id: '424'
- _id: '660'
doi: 10.3389/fpsyg.2025.1574809
intvolume: ' 16'
keyword:
- trust in AI
- trust
- distrust
- human-AI interaction
- Signal Detection Theory
- Bayesian parameter estimation
- image classification
language:
- iso: eng
project:
- _id: '124'
name: 'TRR 318 - C1: TRR 318 - Subproject C1 - Gesundes Misstrauen in Erklärungen'
publication: Frontiers in Psychology
publication_status: published
status: public
title: 'Interacting with fallible AI: Is distrust helpful when receiving AI misclassifications?'
type: journal_article
user_id: '92810'
volume: 16
year: '2025'
...
---
_id: '56983'
abstract:
- lang: eng
text: Detecting the veracity of a statement automatically is a challenge the world
is grappling with due to the vast amount of data spread across the web. Verifying
a given claim typically entails validating it within the framework of supporting
evidence like a retrieved piece of text. Classifying the stance of the text with
respect to the claim is called stance classification. Despite advancements in
automated fact-checking, most systems still rely on a substantial quantity of
labeled training data, which can be costly. In this work, we avoid the costly
training or fine-tuning of models by reusing pre-trained large language models
together with few-shot in-context learning. Since we do not train any model, our
approach ExPrompt is lightweight, demands fewer resources than other stance classification
methods and can serve as a modern baseline for future developments. At the same
time, our evaluation shows that our approach is able to outperform former state-of-the-art
stance classification approaches regarding accuracy by at least 2 percent. Our
scripts and data used in this paper are available at https://github.com/dice-group/ExPrompt.
author:
- first_name: Umair
full_name: Qudus, Umair
id: '83392'
last_name: Qudus
orcid: 0000-0001-6714-8729
- first_name: Michael
full_name: Röder, Michael
id: '67199'
last_name: Röder
orcid: https://orcid.org/0000-0002-8609-8277
- first_name: Daniel
full_name: Vollmers, Daniel
last_name: Vollmers
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Qudus U, Röder M, Vollmers D, Ngonga Ngomo A-C. ExPrompt: Augmenting Prompts
Using Examples as Modern Baseline for Stance Classification. In: Proceedings
of the 33rd ACM International Conference on Information and Knowledge Management.
Vol 9. ACM; 2024:3994-3999. doi:10.1145/3627673.3679923'
apa: 'Qudus, U., Röder, M., Vollmers, D., & Ngonga Ngomo, A.-C. (2024). ExPrompt:
Augmenting Prompts Using Examples as Modern Baseline for Stance Classification.
Proceedings of the 33rd ACM International Conference on Information and Knowledge
Management, 9, 3994–3999. https://doi.org/10.1145/3627673.3679923'
bibtex: '@inproceedings{Qudus_Röder_Vollmers_Ngonga Ngomo_2024, title={ExPrompt:
Augmenting Prompts Using Examples as Modern Baseline for Stance Classification},
volume={9}, DOI={10.1145/3627673.3679923},
booktitle={Proceedings of the 33rd ACM International Conference on Information
and Knowledge Management}, publisher={ACM}, author={Qudus, Umair and Röder, Michael
and Vollmers, Daniel and Ngonga Ngomo, Axel-Cyrille}, year={2024}, pages={3994–3999}
}'
chicago: 'Qudus, Umair, Michael Röder, Daniel Vollmers, and Axel-Cyrille Ngonga
Ngomo. “ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance
Classification.” In Proceedings of the 33rd ACM International Conference on
Information and Knowledge Management, 9:3994–99. ACM, 2024. https://doi.org/10.1145/3627673.3679923.'
ieee: 'U. Qudus, M. Röder, D. Vollmers, and A.-C. Ngonga Ngomo, “ExPrompt: Augmenting
Prompts Using Examples as Modern Baseline for Stance Classification,” in Proceedings
of the 33rd ACM International Conference on Information and Knowledge Management,
Boise, ID, USA, 2024, vol. 9, pp. 3994–3999, doi: 10.1145/3627673.3679923.'
mla: 'Qudus, Umair, et al. “ExPrompt: Augmenting Prompts Using Examples as Modern
Baseline for Stance Classification.” Proceedings of the 33rd ACM International
Conference on Information and Knowledge Management, vol. 9, ACM, 2024, pp.
3994–99, doi:10.1145/3627673.3679923.'
short: 'U. Qudus, M. Röder, D. Vollmers, A.-C. Ngonga Ngomo, in: Proceedings of
the 33rd ACM International Conference on Information and Knowledge Management,
ACM, 2024, pp. 3994–3999.'
conference:
end_date: 2024-10-25
location: Boise, ID, USA
name: 'CIKM ''24: Proceedings of the 33rd ACM International Conference on Information
and Knowledge Management'
start_date: 2024-10-21
date_created: 2024-11-11T13:15:25Z
date_updated: 2025-09-11T09:49:07Z
ddc:
- '006'
doi: 10.1145/3627673.3679923
file:
- access_level: closed
content_type: application/pdf
creator: uqudus
date_created: 2024-11-11T13:24:19Z
date_updated: 2024-11-11T13:24:19Z
file_id: '56984'
file_name: public.pdf
file_size: 531579
relation: main_file
success: 1
file_date_updated: 2024-11-11T13:24:19Z
has_accepted_license: '1'
intvolume: ' 9'
keyword:
- Stance Classification
- Few-shot in-context learning
- Pre-trained large language models
language:
- iso: eng
main_file_link:
- url: https://dl.acm.org/doi/10.1145/3627673.3679923
page: 3994 - 3999
popular_science: '1'
project:
- _id: '412'
name: 'NEBULA: Nutzerzentrierte KI-basierte Erkennung von Fake-News und Fehlinformationen'
publication: Proceedings of the 33rd ACM International Conference on Information and
Knowledge Management
publication_identifier:
isbn:
- 79-8-4007-0436-9/24/10
publication_status: published
publisher: ACM
quality_controlled: '1'
status: public
title: 'ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance
Classification'
type: conference
user_id: '83392'
volume: 9
year: '2024'
...
---
_id: '52660'
abstract:
- lang: eng
text: Application Programming Interfaces (APIs) are the primary mechanism developers
use to obtain access to third-party algorithms and services. Unfortunately, APIs
can be misused, which can have catastrophic consequences, especially if the APIs
provide security-critical functionalities like cryptography. Understanding what
API misuses are, and how they are caused, is important to prevent them, eg, with
API misuse detectors. However, definitions for API misuses and related terms in
literature vary. This paper presents a systematic literature review to clarify
these terms and introduces FUM, a novel Framework for API Usage constraint and
Misuse classification. The literature review revealed that API misuses are violations
of API usage constraints. To address this, we provide unified definitions and
use them to derive FUM. To assess the extent to which FUM aids in determining
and guiding the improvement of an API misuses detector’s capabilities, we performed
a case study on the state-of the-art misuse detection tool CogniCrypt. The study
showed that FUM can be used to properly assess CogniCrypt’s capabilities, identify
weaknesses and assist in deriving mitigations and improvements.
author:
- first_name: Michael
full_name: Schlichtig, Michael
id: '32312'
last_name: Schlichtig
orcid: 0000-0001-6600-6171
- first_name: Steffen
full_name: Sassalla, Steffen
last_name: Sassalla
- first_name: Krishna
full_name: Narasimhan, Krishna
last_name: Narasimhan
- first_name: Eric
full_name: Bodden, Eric
id: '59256'
last_name: Bodden
orcid: 0000-0003-3470-3647
citation:
ama: 'Schlichtig M, Sassalla S, Narasimhan K, Bodden E. Introducing FUM: A Framework
for API Usage Constraint and Misuse Classification. In: Software Engineering
2023. Gesellschaft für Informatik e.V.; 2023:105–106.'
apa: 'Schlichtig, M., Sassalla, S., Narasimhan, K., & Bodden, E. (2023). Introducing
FUM: A Framework for API Usage Constraint and Misuse Classification. In Software
Engineering 2023 (pp. 105–106). Gesellschaft für Informatik e.V.'
bibtex: '@inbook{Schlichtig_Sassalla_Narasimhan_Bodden_2023, place={Bonn}, title={Introducing
FUM: A Framework for API Usage Constraint and Misuse Classification}, booktitle={Software
Engineering 2023}, publisher={Gesellschaft für Informatik e.V.}, author={Schlichtig,
Michael and Sassalla, Steffen and Narasimhan, Krishna and Bodden, Eric}, year={2023},
pages={105–106} }'
chicago: 'Schlichtig, Michael, Steffen Sassalla, Krishna Narasimhan, and Eric Bodden.
“Introducing FUM: A Framework for API Usage Constraint and Misuse Classification.”
In Software Engineering 2023, 105–106. Bonn: Gesellschaft für Informatik
e.V., 2023.'
ieee: 'M. Schlichtig, S. Sassalla, K. Narasimhan, and E. Bodden, “Introducing FUM:
A Framework for API Usage Constraint and Misuse Classification,” in Software
Engineering 2023, Bonn: Gesellschaft für Informatik e.V., 2023, pp. 105–106.'
mla: 'Schlichtig, Michael, et al. “Introducing FUM: A Framework for API Usage Constraint
and Misuse Classification.” Software Engineering 2023, Gesellschaft für
Informatik e.V., 2023, pp. 105–106.'
short: 'M. Schlichtig, S. Sassalla, K. Narasimhan, E. Bodden, in: Software Engineering
2023, Gesellschaft für Informatik e.V., Bonn, 2023, pp. 105–106.'
date_created: 2024-03-20T09:22:27Z
date_updated: 2024-03-20T09:25:46Z
department:
- _id: '76'
keyword:
- API misuses API usage constraints
- classification framework
- API misuse detection
- static analysis
language:
- iso: eng
main_file_link:
- url: https://dl.gi.de/items/c4825557-cf3d-4038-933a-d8f95fd324a2
page: 105–106
place: Bonn
publication: Software Engineering 2023
publication_identifier:
isbn:
- 978-3-88579-726-5
publisher: Gesellschaft für Informatik e.V.
status: public
title: 'Introducing FUM: A Framework for API Usage Constraint and Misuse Classification'
type: book_chapter
user_id: '32312'
year: '2023'
...
---
_id: '53801'
abstract:
- lang: eng
text: 'In this study, we evaluate the impact of gender-biased data from German-language
physician reviews on the fairness of fine-tuned language models. For two different
downstream tasks, we use data reported to be gender biased and aggregate it with
annotations. First, we propose a new approach to aspect-based sentiment analysis
that allows identifying, extracting, and classifying implicit and explicit aspect
phrases and their polarity within a single model. The second task we present is
grade prediction, where we predict the overall grade of a review on the basis
of the review text. For both tasks, we train numerous transformer models and evaluate
their performance. The aggregation of sensitive attributes, such as a physician’s
gender and migration background, with individual text reviews allows us to measure
the performance of the models with respect to these sensitive groups. These group-wise
performance measures act as extrinsic bias measures for our downstream tasks.
In addition, we translate several gender-specific templates of the intrinsic bias
metrics into the German language and evaluate our fine-tuned models. Based on
this set of tasks, fine-tuned models, and intrinsic and extrinsic bias measures,
we perform correlation analyses between intrinsic and extrinsic bias measures.
In terms of sensitive groups and effect sizes, our bias measure results show different
directions. Furthermore, correlations between measures of intrinsic and extrinsic
bias can be observed in different directions. This leads us to conclude that gender-biased
data does not inherently lead to biased models. Other variables, such as template
dependency for intrinsic measures and label distribution in the data, must be
taken into account as they strongly influence the metric results. Therefore, we
suggest that metrics and templates should be chosen according to the given task
and the biases to be assessed. '
article_number: '102235'
article_type: original
author:
- first_name: Joschka
full_name: Kersting, Joschka
id: '58701'
last_name: Kersting
- first_name: Falk
full_name: Maoro, Falk
last_name: Maoro
- first_name: Michaela
full_name: Geierhos, Michaela
last_name: Geierhos
citation:
ama: 'Kersting J, Maoro F, Geierhos M. Towards comparable ratings: Exploring bias
in German physician reviews. Data & Knowledge Engineering. 2023;148.
doi:10.1016/j.datak.2023.102235'
apa: 'Kersting, J., Maoro, F., & Geierhos, M. (2023). Towards comparable ratings:
Exploring bias in German physician reviews. Data & Knowledge Engineering,
148, Article 102235. https://doi.org/10.1016/j.datak.2023.102235'
bibtex: '@article{Kersting_Maoro_Geierhos_2023, title={Towards comparable ratings:
Exploring bias in German physician reviews}, volume={148}, DOI={10.1016/j.datak.2023.102235},
number={102235}, journal={Data & Knowledge Engineering}, publisher={Elsevier},
author={Kersting, Joschka and Maoro, Falk and Geierhos, Michaela}, year={2023}
}'
chicago: 'Kersting, Joschka, Falk Maoro, and Michaela Geierhos. “Towards Comparable
Ratings: Exploring Bias in German Physician Reviews.” Data & Knowledge
Engineering 148 (2023). https://doi.org/10.1016/j.datak.2023.102235.'
ieee: 'J. Kersting, F. Maoro, and M. Geierhos, “Towards comparable ratings: Exploring
bias in German physician reviews,” Data & Knowledge Engineering, vol.
148, Art. no. 102235, 2023, doi: 10.1016/j.datak.2023.102235.'
mla: 'Kersting, Joschka, et al. “Towards Comparable Ratings: Exploring Bias in German
Physician Reviews.” Data & Knowledge Engineering, vol. 148, 102235,
Elsevier, 2023, doi:10.1016/j.datak.2023.102235.'
short: J. Kersting, F. Maoro, M. Geierhos, Data & Knowledge Engineering 148
(2023).
date_created: 2024-04-30T12:30:56Z
date_updated: 2024-04-30T12:41:14Z
ddc:
- '004'
department:
- _id: '579'
doi: 10.1016/j.datak.2023.102235
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2024-04-30T12:34:35Z
date_updated: 2024-04-30T12:34:35Z
file_id: '53802'
file_name: Kersting 2023.pdf
file_size: 1381398
relation: main_file
success: 1
file_date_updated: 2024-04-30T12:34:35Z
funded_apc: '1'
has_accepted_license: '1'
intvolume: ' 148'
keyword:
- Language model fairness
- Aspect phrase classification
- Grade prediction
- Physician reviews
language:
- iso: eng
main_file_link:
- open_access: '1'
url: ' https://doi.org/10.1016/j.datak.2023.102235 '
oa: '1'
project:
- _id: '1'
grant_number: '160364472'
name: 'SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen
in dynamischen Märkten '
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '9'
grant_number: '160364472'
name: 'SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject
B1)'
publication: Data & Knowledge Engineering
publication_identifier:
issn:
- 0169-023X
publication_status: published
publisher: Elsevier
status: public
title: 'Towards comparable ratings: Exploring bias in German physician reviews'
type: journal_article
user_id: '58701'
volume: 148
year: '2023'
...
---
_id: '31133'
abstract:
- lang: eng
text: Application Programming Interfaces (APIs) are the primary mechanism that developers
use to obtain access to third-party algorithms and services. Unfortunately, APIs
can be misused, which can have catastrophic consequences, especially if the APIs
provide security-critical functionalities like cryptography. Understanding what
API misuses are, and for what reasons they are caused, is important to prevent
them, e.g., with API misuse detectors. However, definitions and nominations for
API misuses and related terms in literature vary and are diverse. This paper addresses
the problem of scattered knowledge and definitions of API misuses by presenting
a systematic literature review on the subject and introducing FUM, a novel Framework
for API Usage constraint and Misuse classification. The literature review revealed
that API misuses are violations of API usage constraints. To capture this, we
provide unified definitions and use them to derive FUM. To assess the extent to
which FUM aids in determining and guiding the improvement of an API misuses detectors'
capabilities, we performed a case study on CogniCrypt, a state-of-the-art misuse
detector for cryptographic APIs. The study showed that FUM can be used to properly
assess CogniCrypt's capabilities, identify weaknesses and assist in deriving mitigations
and improvements. And it appears that also more generally FUM can aid the development
and improvement of misuse detection tools.
author:
- first_name: Michael
full_name: Schlichtig, Michael
id: '32312'
last_name: Schlichtig
orcid: 0000-0001-6600-6171
- first_name: Steffen
full_name: Sassalla, Steffen
last_name: Sassalla
- first_name: Krishna
full_name: Narasimhan, Krishna
last_name: Narasimhan
- first_name: Eric
full_name: Bodden, Eric
id: '59256'
last_name: Bodden
orcid: 0000-0003-3470-3647
citation:
ama: 'Schlichtig M, Sassalla S, Narasimhan K, Bodden E. FUM - A Framework for API
Usage constraint and Misuse Classification. In: 2022 IEEE International Conference
on Software Analysis, Evolution and Reengineering (SANER). ; 2022:673-684.
doi:https://doi.org/10.1109/SANER53432.2022.00085'
apa: Schlichtig, M., Sassalla, S., Narasimhan, K., & Bodden, E. (2022). FUM
- A Framework for API Usage constraint and Misuse Classification. 2022 IEEE
International Conference on Software Analysis, Evolution and Reengineering (SANER),
673–684. https://doi.org/10.1109/SANER53432.2022.00085
bibtex: '@inproceedings{Schlichtig_Sassalla_Narasimhan_Bodden_2022, title={FUM -
A Framework for API Usage constraint and Misuse Classification}, DOI={https://doi.org/10.1109/SANER53432.2022.00085},
booktitle={2022 IEEE International Conference on Software Analysis, Evolution
and Reengineering (SANER)}, author={Schlichtig, Michael and Sassalla, Steffen
and Narasimhan, Krishna and Bodden, Eric}, year={2022}, pages={673–684} }'
chicago: Schlichtig, Michael, Steffen Sassalla, Krishna Narasimhan, and Eric Bodden.
“FUM - A Framework for API Usage Constraint and Misuse Classification.” In 2022
IEEE International Conference on Software Analysis, Evolution and Reengineering
(SANER), 673–84, 2022. https://doi.org/10.1109/SANER53432.2022.00085.
ieee: 'M. Schlichtig, S. Sassalla, K. Narasimhan, and E. Bodden, “FUM - A Framework
for API Usage constraint and Misuse Classification,” in 2022 IEEE International
Conference on Software Analysis, Evolution and Reengineering (SANER), 2022,
pp. 673–684, doi: https://doi.org/10.1109/SANER53432.2022.00085.'
mla: Schlichtig, Michael, et al. “FUM - A Framework for API Usage Constraint and
Misuse Classification.” 2022 IEEE International Conference on Software Analysis,
Evolution and Reengineering (SANER), 2022, pp. 673–84, doi:https://doi.org/10.1109/SANER53432.2022.00085.
short: 'M. Schlichtig, S. Sassalla, K. Narasimhan, E. Bodden, in: 2022 IEEE International
Conference on Software Analysis, Evolution and Reengineering (SANER), 2022, pp.
673–684.'
date_created: 2022-05-09T13:04:10Z
date_updated: 2022-07-26T11:42:30Z
department:
- _id: '76'
doi: https://doi.org/10.1109/SANER53432.2022.00085
keyword:
- API misuses
- API usage constraints
- classification framework
- API misuse detection
- static analysis
language:
- iso: eng
page: 673 - 684
publication: 2022 IEEE International Conference on Software Analysis, Evolution and
Reengineering (SANER)
quality_controlled: '1'
related_material:
link:
- relation: confirmation
url: https://ieeexplore.ieee.org/document/9825763
status: public
title: FUM - A Framework for API Usage constraint and Misuse Classification
type: conference
user_id: '32312'
year: '2022'
...
---
_id: '48878'
abstract:
- lang: eng
text: Due to the rise of continuous data-generating applications, analyzing data
streams has gained increasing attention over the past decades. A core research
area in stream data is stream classification, which categorizes or detects data
points within an evolving stream of observations. Areas of stream classification
are diverse\textemdash ranging, e.g., from monitoring sensor data to analyzing
a wide range of (social) media applications. Research in stream classification
is related to developing methods that adapt to the changing and potentially volatile
data stream. It focuses on individual aspects of the stream classification pipeline,
e.g., designing suitable algorithm architectures, an efficient train and test
procedure, or detecting so-called concept drifts. As a result of the many different
research questions and strands, the field is challenging to grasp, especially
for beginners. This survey explores, summarizes, and categorizes work within the
domain of stream classification and identifies core research threads over the
past few years. It is structured based on the stream classification process to
facilitate coordination within this complex topic, including common application
scenarios and benchmarking data sets. Thus, both newcomers to the field and experts
who want to widen their scope can gain (additional) insight into this research
area and find starting points and pointers to more in-depth literature on specific
issues and research directions in the field.
author:
- first_name: Lena
full_name: Clever, Lena
last_name: Clever
- first_name: Janina Susanne
full_name: Pohl, Janina Susanne
last_name: Pohl
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Heike
full_name: Trautmann, Heike
last_name: Trautmann
citation:
ama: 'Clever L, Pohl JS, Bossek J, Kerschke P, Trautmann H. Process-Oriented Stream
Classification Pipeline: A Literature Review. Applied Sciences. 2022;12(18):9094.
doi:10.3390/app12189094'
apa: 'Clever, L., Pohl, J. S., Bossek, J., Kerschke, P., & Trautmann, H. (2022).
Process-Oriented Stream Classification Pipeline: A Literature Review. Applied
Sciences, 12(18), 9094. https://doi.org/10.3390/app12189094'
bibtex: '@article{Clever_Pohl_Bossek_Kerschke_Trautmann_2022, title={Process-Oriented
Stream Classification Pipeline: A Literature Review}, volume={12}, DOI={10.3390/app12189094},
number={18}, journal={Applied Sciences}, publisher={{Multidisciplinary Digital
Publishing Institute}}, author={Clever, Lena and Pohl, Janina Susanne and Bossek,
Jakob and Kerschke, Pascal and Trautmann, Heike}, year={2022}, pages={9094} }'
chicago: 'Clever, Lena, Janina Susanne Pohl, Jakob Bossek, Pascal Kerschke, and
Heike Trautmann. “Process-Oriented Stream Classification Pipeline: A Literature
Review.” Applied Sciences 12, no. 18 (2022): 9094. https://doi.org/10.3390/app12189094.'
ieee: 'L. Clever, J. S. Pohl, J. Bossek, P. Kerschke, and H. Trautmann, “Process-Oriented
Stream Classification Pipeline: A Literature Review,” Applied Sciences,
vol. 12, no. 18, p. 9094, 2022, doi: 10.3390/app12189094.'
mla: 'Clever, Lena, et al. “Process-Oriented Stream Classification Pipeline: A Literature
Review.” Applied Sciences, vol. 12, no. 18, {Multidisciplinary Digital
Publishing Institute}, 2022, p. 9094, doi:10.3390/app12189094.'
short: L. Clever, J.S. Pohl, J. Bossek, P. Kerschke, H. Trautmann, Applied Sciences
12 (2022) 9094.
date_created: 2023-11-14T15:58:57Z
date_updated: 2023-12-13T10:50:56Z
department:
- _id: '819'
doi: 10.3390/app12189094
intvolume: ' 12'
issue: '18'
keyword:
- big data
- data mining
- data stream analysis
- machine learning
- stream classification
- supervised learning
language:
- iso: eng
page: '9094'
publication: Applied Sciences
publication_identifier:
issn:
- 2076-3417
publisher: '{Multidisciplinary Digital Publishing Institute}'
status: public
title: 'Process-Oriented Stream Classification Pipeline: A Literature Review'
type: journal_article
user_id: '102979'
volume: 12
year: '2022'
...
---
_id: '21004'
abstract:
- lang: eng
text: 'Automated machine learning (AutoML) supports the algorithmic construction
and data-specific customization of machine learning pipelines, including the selection,
combination, and parametrization of machine learning algorithms as main constituents.
Generally speaking, AutoML approaches comprise two major components: a search
space model and an optimizer for traversing the space. Recent approaches have
shown impressive results in the realm of supervised learning, most notably (single-label)
classification (SLC). Moreover, first attempts at extending these approaches towards
multi-label classification (MLC) have been made. While the space of candidate
pipelines is already huge in SLC, the complexity of the search space is raised
to an even higher power in MLC. One may wonder, therefore, whether and to what
extent optimizers established for SLC can scale to this increased complexity,
and how they compare to each other. This paper makes the following contributions:
First, we survey existing approaches to AutoML for MLC. Second, we augment these
approaches with optimizers not previously tried for MLC. Third, we propose a benchmarking
framework that supports a fair and systematic comparison. Fourth, we conduct an
extensive experimental study, evaluating the methods on a suite of MLC problems.
We find a grammar-based best-first search to compare favorably to other optimizers.'
author:
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Alexander
full_name: Tornede, Alexander
id: '38209'
last_name: Tornede
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Wever MD, Tornede A, Mohr F, Hüllermeier E. AutoML for Multi-Label Classification:
Overview and Empirical Evaluation. IEEE Transactions on Pattern Analysis and
Machine Intelligence. Published online 2021:1-1. doi:10.1109/tpami.2021.3051276'
apa: 'Wever, M. D., Tornede, A., Mohr, F., & Hüllermeier, E. (2021). AutoML
for Multi-Label Classification: Overview and Empirical Evaluation. IEEE Transactions
on Pattern Analysis and Machine Intelligence, 1–1. https://doi.org/10.1109/tpami.2021.3051276'
bibtex: '@article{Wever_Tornede_Mohr_Hüllermeier_2021, title={AutoML for Multi-Label
Classification: Overview and Empirical Evaluation}, DOI={10.1109/tpami.2021.3051276},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, author={Wever,
Marcel Dominik and Tornede, Alexander and Mohr, Felix and Hüllermeier, Eyke},
year={2021}, pages={1–1} }'
chicago: 'Wever, Marcel Dominik, Alexander Tornede, Felix Mohr, and Eyke Hüllermeier.
“AutoML for Multi-Label Classification: Overview and Empirical Evaluation.” IEEE
Transactions on Pattern Analysis and Machine Intelligence, 2021, 1–1. https://doi.org/10.1109/tpami.2021.3051276.'
ieee: 'M. D. Wever, A. Tornede, F. Mohr, and E. Hüllermeier, “AutoML for Multi-Label
Classification: Overview and Empirical Evaluation,” IEEE Transactions on Pattern
Analysis and Machine Intelligence, pp. 1–1, 2021, doi: 10.1109/tpami.2021.3051276.'
mla: 'Wever, Marcel Dominik, et al. “AutoML for Multi-Label Classification: Overview
and Empirical Evaluation.” IEEE Transactions on Pattern Analysis and Machine
Intelligence, 2021, pp. 1–1, doi:10.1109/tpami.2021.3051276.'
short: M.D. Wever, A. Tornede, F. Mohr, E. Hüllermeier, IEEE Transactions on Pattern
Analysis and Machine Intelligence (2021) 1–1.
date_created: 2021-01-16T14:48:13Z
date_updated: 2022-01-06T06:54:42Z
department:
- _id: '34'
- _id: '355'
- _id: '26'
doi: 10.1109/tpami.2021.3051276
keyword:
- Automated Machine Learning
- Multi Label Classification
- Hierarchical Planning
- Bayesian Optimization
language:
- iso: eng
page: 1-1
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: IEEE Transactions on Pattern Analysis and Machine Intelligence
publication_identifier:
issn:
- 0162-8828
- 2160-9292
- 1939-3539
publication_status: published
status: public
title: 'AutoML for Multi-Label Classification: Overview and Empirical Evaluation'
type: journal_article
user_id: '5786'
year: '2021'
...
---
_id: '20212'
abstract:
- lang: eng
text: "Ideational impact refers to the uptake of a paper's ideas and concepts by
subsequent research. It is defined in stark contrast to total citation impact,
a measure predominantly used in research evaluation that assumes that all citations
are equal. Understanding ideational impact is critical for evaluating research
impact and understanding how scientific disciplines build a cumulative tradition.
Research has only recently developed automated citation classification techniques
to distinguish between different types of citations and generally does not emphasize
the conceptual content of the citations and its ideational impact. To address
this problem, we develop Deep Content-enriched Ideational Impact Classification
(Deep-CENIC) as the first automated approach for ideational impact classification
to support researchers' literature search practices. We evaluate Deep-CENIC on
1,256 papers citing 24 information systems review articles from the IT business
value domain. We show that Deep-CENIC significantly outperforms state-of-the-art
benchmark models. We contribute to information systems research by operationalizing
the concept of ideational impact, designing a recommender system for academic
papers based on deep learning techniques, and empirically exploring the ideational
impact of the IT business value domain.\r\n"
article_number: '113432'
author:
- first_name: Julian
full_name: Prester, Julian
last_name: Prester
- first_name: Gerit
full_name: Wagner, Gerit
last_name: Wagner
- first_name: Guido
full_name: Schryen, Guido
id: '72850'
last_name: Schryen
- first_name: Nik Rushdi
full_name: Hassan, Nik Rushdi
last_name: Hassan
citation:
ama: 'Prester J, Wagner G, Schryen G, Hassan NR. Classifying the Ideational Impact
of Information Systems Review Articles: A Content-Enriched Deep Learning Approach.
Decision Support Systems. 2021;140(January).'
apa: 'Prester, J., Wagner, G., Schryen, G., & Hassan, N. R. (2021). Classifying
the Ideational Impact of Information Systems Review Articles: A Content-Enriched
Deep Learning Approach. Decision Support Systems, 140(January),
Article 113432.'
bibtex: '@article{Prester_Wagner_Schryen_Hassan_2021, title={Classifying the Ideational
Impact of Information Systems Review Articles: A Content-Enriched Deep Learning
Approach}, volume={140}, number={January113432}, journal={Decision Support Systems},
author={Prester, Julian and Wagner, Gerit and Schryen, Guido and Hassan, Nik Rushdi},
year={2021} }'
chicago: 'Prester, Julian, Gerit Wagner, Guido Schryen, and Nik Rushdi Hassan. “Classifying
the Ideational Impact of Information Systems Review Articles: A Content-Enriched
Deep Learning Approach.” Decision Support Systems 140, no. January (2021).'
ieee: 'J. Prester, G. Wagner, G. Schryen, and N. R. Hassan, “Classifying the Ideational
Impact of Information Systems Review Articles: A Content-Enriched Deep Learning
Approach,” Decision Support Systems, vol. 140, no. January, Art. no. 113432,
2021.'
mla: 'Prester, Julian, et al. “Classifying the Ideational Impact of Information
Systems Review Articles: A Content-Enriched Deep Learning Approach.” Decision
Support Systems, vol. 140, no. January, 113432, 2021.'
short: J. Prester, G. Wagner, G. Schryen, N.R. Hassan, Decision Support Systems
140 (2021).
date_created: 2020-10-27T13:28:21Z
date_updated: 2022-06-10T06:55:32Z
ddc:
- '000'
department:
- _id: '277'
file:
- access_level: open_access
content_type: application/pdf
creator: hsiemes
date_created: 2020-10-27T13:31:01Z
date_updated: 2020-10-27T13:31:01Z
file_id: '20213'
file_name: DECSUP-D-20-00312 - PREPUBLICATION.pdf
file_size: 440903
relation: main_file
file_date_updated: 2020-10-27T13:31:01Z
has_accepted_license: '1'
intvolume: ' 140'
issue: January
keyword:
- Ideational impact
- citation classification
- academic recommender systems
- natural language processing
- deep learning
- cumulative tradition
language:
- iso: eng
oa: '1'
publication: Decision Support Systems
status: public
title: 'Classifying the Ideational Impact of Information Systems Review Articles:
A Content-Enriched Deep Learning Approach'
type: journal_article
user_id: '72850'
volume: 140
year: '2021'
...
---
_id: '24547'
abstract:
- lang: eng
text: 'Over the last years, several approaches for the data-driven estimation of
expected possession value (EPV) in basketball and association football (soccer)
have been proposed. In this paper, we develop and evaluate PIVOT: the first such
framework for team handball. Accounting for the fast-paced, dynamic nature and
relative data scarcity of hand- ball, we propose a parsimonious end-to-end deep
learning architecture that relies solely on tracking data. This efficient approach
is capable of predicting the probability that a team will score within the near
future given the fine-grained spatio-temporal distribution of all players and
the ball over the last seconds of the game. Our experiments indicate that PIVOT
is able to produce accurate and calibrated probability estimates, even when trained
on a relatively small dataset. We also showcase two interactive applications of
PIVOT for valuing actual and counterfactual player decisions and actions in real-time.'
author:
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
- first_name: Matthew
full_name: Caron, Matthew
id: '60721'
last_name: Caron
- first_name: Michael
full_name: Döring, Michael
last_name: Döring
- first_name: Tim
full_name: Heuwinkel, Tim
last_name: Heuwinkel
- first_name: Jochen
full_name: Baumeister, Jochen
id: '46'
last_name: Baumeister
orcid: 0000-0003-2683-5826
citation:
ama: 'Müller O, Caron M, Döring M, Heuwinkel T, Baumeister J. PIVOT: A Parsimonious
End-to-End Learning Framework for Valuing Player Actions in Handball using Tracking
Data. In: 8th Workshop on Machine Learning and Data Mining for Sports Analytics
(ECML PKDD 2021).'
apa: 'Müller, O., Caron, M., Döring, M., Heuwinkel, T., & Baumeister, J. (n.d.).
PIVOT: A Parsimonious End-to-End Learning Framework for Valuing Player Actions
in Handball using Tracking Data. 8th Workshop on Machine Learning and Data
Mining for Sports Analytics (ECML PKDD 2021). European Conference on Machine
Learning and Principles and Practice of Knowledge Discovery (ECML PKDD 2021),
Online.'
bibtex: '@inproceedings{Müller_Caron_Döring_Heuwinkel_Baumeister, title={PIVOT:
A Parsimonious End-to-End Learning Framework for Valuing Player Actions in Handball
using Tracking Data}, booktitle={8th Workshop on Machine Learning and Data Mining
for Sports Analytics (ECML PKDD 2021)}, author={Müller, Oliver and Caron, Matthew
and Döring, Michael and Heuwinkel, Tim and Baumeister, Jochen} }'
chicago: 'Müller, Oliver, Matthew Caron, Michael Döring, Tim Heuwinkel, and Jochen
Baumeister. “PIVOT: A Parsimonious End-to-End Learning Framework for Valuing Player
Actions in Handball Using Tracking Data.” In 8th Workshop on Machine Learning
and Data Mining for Sports Analytics (ECML PKDD 2021), n.d.'
ieee: 'O. Müller, M. Caron, M. Döring, T. Heuwinkel, and J. Baumeister, “PIVOT:
A Parsimonious End-to-End Learning Framework for Valuing Player Actions in Handball
using Tracking Data,” presented at the European Conference on Machine Learning
and Principles and Practice of Knowledge Discovery (ECML PKDD 2021), Online.'
mla: 'Müller, Oliver, et al. “PIVOT: A Parsimonious End-to-End Learning Framework
for Valuing Player Actions in Handball Using Tracking Data.” 8th Workshop on
Machine Learning and Data Mining for Sports Analytics (ECML PKDD 2021).'
short: 'O. Müller, M. Caron, M. Döring, T. Heuwinkel, J. Baumeister, in: 8th Workshop
on Machine Learning and Data Mining for Sports Analytics (ECML PKDD 2021), n.d.'
conference:
end_date: 2021-09-17
location: Online
name: European Conference on Machine Learning and Principles and Practice of Knowledge
Discovery (ECML PKDD 2021)
start_date: 2021-09-13
date_created: 2021-09-16T08:33:04Z
date_updated: 2023-02-28T08:58:24Z
department:
- _id: '196'
- _id: '172'
keyword:
- expected possession value
- handball
- tracking data
- time series classification
- deep learning
language:
- iso: eng
main_file_link:
- url: https://dtai.cs.kuleuven.be/events/MLSA21/papers/MLSA21_paper_muller.pdf
publication: 8th Workshop on Machine Learning and Data Mining for Sports Analytics
(ECML PKDD 2021)
publication_status: inpress
status: public
title: 'PIVOT: A Parsimonious End-to-End Learning Framework for Valuing Player Actions
in Handball using Tracking Data'
type: conference
user_id: '60721'
year: '2021'
...
---
_id: '27111'
abstract:
- lang: eng
text: In the industry 4.0 era, there is a growing need to transform unstructured
data acquired by a multitude of sources into information and subsequently into
knowledge to improve the quality of manufactured products, to boost production,
for predictive maintenance, etc. Data-driven approaches, such as machine learning
techniques, are typically employed to model the underlying relationship from data.
However, an increase in model accuracy with state-of-the-art methods, such as
deep convolutional neural networks, results in less interpretability and transparency.
Due to the ease of implementation, interpretation and transparency to both domain
experts and non-experts, a rule-based method is proposed in this paper, for prognostics
and health management (PHM) and specifically for diagnostics. The proposed method
utilizes the most relevant sensor signals acquired via feature extraction and
selection techniques and expert knowledge. As a case study, the presented method
is evaluated on data from a real-world quality control set-up provided by the
European prognostics and health management society (PHME) at the conference’s
2021 data challenge. With the proposed method, our team took the third place,
capable of successfully diagnosing different fault modes, irrespective of varying
conditions.
author:
- first_name: Osarenren Kennedy
full_name: Aimiyekagbon, Osarenren Kennedy
id: '9557'
last_name: Aimiyekagbon
- first_name: Lars
full_name: Muth, Lars
id: '77313'
last_name: Muth
orcid: 0000-0002-2938-5616
- first_name: Meike Claudia
full_name: Wohlleben, Meike Claudia
id: '43991'
last_name: Wohlleben
orcid: 0009-0009-9767-7168
- first_name: Amelie
full_name: Bender, Amelie
id: '54290'
last_name: Bender
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: 'Aimiyekagbon OK, Muth L, Wohlleben MC, Bender A, Sextro W. Rule-based Diagnostics
of a Production Line. In: Do P, King S, Fink O, eds. Proceedings of the European
Conference of the PHM Society 2021. Vol 6. ; 2021:527-536. doi:10.36001/phme.2021.v6i1.3042'
apa: Aimiyekagbon, O. K., Muth, L., Wohlleben, M. C., Bender, A., & Sextro,
W. (2021). Rule-based Diagnostics of a Production Line. In P. Do, S. King, &
O. Fink (Eds.), Proceedings of the European Conference of the PHM Society 2021
(Vol. 6, Issue 1, pp. 527–536). https://doi.org/10.36001/phme.2021.v6i1.3042
bibtex: '@inproceedings{Aimiyekagbon_Muth_Wohlleben_Bender_Sextro_2021, title={Rule-based
Diagnostics of a Production Line}, volume={6}, DOI={10.36001/phme.2021.v6i1.3042},
number={1}, booktitle={Proceedings of the European Conference of the PHM Society
2021}, author={Aimiyekagbon, Osarenren Kennedy and Muth, Lars and Wohlleben, Meike
Claudia and Bender, Amelie and Sextro, Walter}, editor={Do, Phuc and King, Steve
and Fink, Olga}, year={2021}, pages={527–536} }'
chicago: Aimiyekagbon, Osarenren Kennedy, Lars Muth, Meike Claudia Wohlleben, Amelie
Bender, and Walter Sextro. “Rule-Based Diagnostics of a Production Line.” In Proceedings
of the European Conference of the PHM Society 2021, edited by Phuc Do, Steve
King, and Olga Fink, 6:527–36, 2021. https://doi.org/10.36001/phme.2021.v6i1.3042.
ieee: 'O. K. Aimiyekagbon, L. Muth, M. C. Wohlleben, A. Bender, and W. Sextro, “Rule-based
Diagnostics of a Production Line,” in Proceedings of the European Conference
of the PHM Society 2021, 2021, vol. 6, no. 1, pp. 527–536, doi: 10.36001/phme.2021.v6i1.3042.'
mla: Aimiyekagbon, Osarenren Kennedy, et al. “Rule-Based Diagnostics of a Production
Line.” Proceedings of the European Conference of the PHM Society 2021,
edited by Phuc Do et al., vol. 6, no. 1, 2021, pp. 527–36, doi:10.36001/phme.2021.v6i1.3042.
short: 'O.K. Aimiyekagbon, L. Muth, M.C. Wohlleben, A. Bender, W. Sextro, in: P.
Do, S. King, O. Fink (Eds.), Proceedings of the European Conference of the PHM
Society 2021, 2021, pp. 527–536.'
conference:
name: PHM Society European Conference
date_created: 2021-11-03T12:26:39Z
date_updated: 2023-09-22T09:13:01Z
department:
- _id: '151'
doi: 10.36001/phme.2021.v6i1.3042
editor:
- first_name: Phuc
full_name: Do, Phuc
last_name: Do
- first_name: Steve
full_name: King, Steve
last_name: King
- first_name: Olga
full_name: Fink, Olga
last_name: Fink
intvolume: ' 6'
issue: '1'
keyword:
- PHME 2021
- Feature Selection Classification
- Feature Selection Clustering
- Interpretable Model
- Transparent Model
- Industry 4.0
- Real-World Diagnostics
- Quality Control
- Predictive Maintenance
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://papers.phmsociety.org/index.php/phme/article/download/3042/1812
oa: '1'
page: 527-536
publication: Proceedings of the European Conference of the PHM Society 2021
publication_status: published
quality_controlled: '1'
status: public
title: Rule-based Diagnostics of a Production Line
type: conference
user_id: '9557'
volume: 6
year: '2021'
...
---
_id: '2109'
abstract:
- lang: eng
text: In multinomial classification, reduction techniques are commonly used to decompose
the original learning problem into several simpler problems. For example, by recursively
bisecting the original set of classes, so-called nested dichotomies define a set
of binary classification problems that are organized in the structure of a binary
tree. In contrast to the existing one-shot heuristics for constructing nested
dichotomies and motivated by recent work on algorithm configuration, we propose
a genetic algorithm for optimizing the structure of such dichotomies. A key component
of this approach is the proposed genetic representation that facilitates the application
of standard genetic operators, while still supporting the exchange of partial
solutions under recombination. We evaluate the approach in an extensive experimental
study, showing that it yields classifiers with superior generalization performance.
author:
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Wever MD, Mohr F, Hüllermeier E. Ensembles of Evolved Nested Dichotomies for
Classification. In: Proceedings of the Genetic and Evolutionary Computation
Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018. Kyoto, Japan: ACM;
2018. doi:10.1145/3205455.3205562'
apa: 'Wever, M. D., Mohr, F., & Hüllermeier, E. (2018). Ensembles of Evolved
Nested Dichotomies for Classification. In Proceedings of the Genetic and Evolutionary
Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018. Kyoto,
Japan: ACM. https://doi.org/10.1145/3205455.3205562'
bibtex: '@inproceedings{Wever_Mohr_Hüllermeier_2018, place={Kyoto, Japan}, title={Ensembles
of Evolved Nested Dichotomies for Classification}, DOI={10.1145/3205455.3205562},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference,
GECCO 2018, Kyoto, Japan, July 15-19, 2018}, publisher={ACM}, author={Wever, Marcel
Dominik and Mohr, Felix and Hüllermeier, Eyke}, year={2018} }'
chicago: 'Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “Ensembles of
Evolved Nested Dichotomies for Classification.” In Proceedings of the Genetic
and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19,
2018. Kyoto, Japan: ACM, 2018. https://doi.org/10.1145/3205455.3205562.'
ieee: M. D. Wever, F. Mohr, and E. Hüllermeier, “Ensembles of Evolved Nested Dichotomies
for Classification,” in Proceedings of the Genetic and Evolutionary Computation
Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018, Kyoto, Japan, 2018.
mla: Wever, Marcel Dominik, et al. “Ensembles of Evolved Nested Dichotomies for
Classification.” Proceedings of the Genetic and Evolutionary Computation Conference,
GECCO 2018, Kyoto, Japan, July 15-19, 2018, ACM, 2018, doi:10.1145/3205455.3205562.
short: 'M.D. Wever, F. Mohr, E. Hüllermeier, in: Proceedings of the Genetic and
Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018,
ACM, Kyoto, Japan, 2018.'
conference:
end_date: 2018-07-19
location: Kyoto, Japan
name: GECCO 2018
start_date: 2018-07-15
date_created: 2018-03-31T13:51:23Z
date_updated: 2022-01-06T06:54:45Z
ddc:
- '000'
department:
- _id: '355'
doi: 10.1145/3205455.3205562
file:
- access_level: closed
content_type: application/pdf
creator: ups
date_created: 2018-11-02T14:33:54Z
date_updated: 2018-11-02T14:33:54Z
file_id: '5275'
file_name: p561-wever.pdf
file_size: 875404
relation: main_file
success: 1
file_date_updated: 2018-11-02T14:33:54Z
has_accepted_license: '1'
keyword:
- Classification
- Hierarchical Decomposition
- Indirect Encoding
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://dl.acm.org/citation.cfm?doid=3205455.3205562
oa: '1'
place: Kyoto, Japan
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO
2018, Kyoto, Japan, July 15-19, 2018
publication_status: published
publisher: ACM
status: public
title: Ensembles of Evolved Nested Dichotomies for Classification
type: conference
user_id: '33176'
year: '2018'
...
---
_id: '5617'
abstract:
- lang: eng
text: CAPTCHAs are challenge-response tests that aim at preventing unwanted machines,
including bots, from accessing web services while providing easy access for humans.
Recent advances in artificial-intelligence based attacks show that the level of
security provided by many state-of-the-art text-based CAPTCHAs is declining. At
the same time, techniques for distorting and obscuring the text, which are used
to maintain the level of security, make text-based CAPTCHAs diffcult to solve
for humans, and thereby further degrade usability. The need for developing alternative
types of CAPTCHAs which improve both, the current security and usability levels,
has been emphasized by several researchers. With this study, we contribute to
research through (1) the development of two new face recognition CAPTCHAs (Farett-Gender
and Farett-Gender&Age), (2) the security analysis of both procedures, and (3)
the provision of empirical evidence that one of the suggested CAPTCHAs (Farett-Gender)
is similar to Google's reCAPTCHA and better than KCAPTCHA concerning effectiveness
(error rates), superior to both regarding learnability and satisfaction but not
effciency.
author:
- first_name: Guido
full_name: Schryen, Guido
id: '72850'
last_name: Schryen
- first_name: Gerit
full_name: Wagner, Gerit
last_name: Wagner
- first_name: Alexander
full_name: Schlegel, Alexander
last_name: Schlegel
citation:
ama: 'Schryen G, Wagner G, Schlegel A. Development of two novel face-recognition
CAPTCHAs: a security and usability study. Computers & Security. 2016;60(July):95-116.'
apa: 'Schryen, G., Wagner, G., & Schlegel, A. (2016). Development of two novel
face-recognition CAPTCHAs: a security and usability study. Computers &
Security, 60(July), 95–116.'
bibtex: '@article{Schryen_Wagner_Schlegel_2016, title={Development of two novel
face-recognition CAPTCHAs: a security and usability study}, volume={60}, number={July},
journal={Computers & Security}, publisher={Elsevier}, author={Schryen, Guido
and Wagner, Gerit and Schlegel, Alexander}, year={2016}, pages={95–116} }'
chicago: 'Schryen, Guido, Gerit Wagner, and Alexander Schlegel. “Development of
Two Novel Face-Recognition CAPTCHAs: A Security and Usability Study.” Computers
& Security 60, no. July (2016): 95–116.'
ieee: 'G. Schryen, G. Wagner, and A. Schlegel, “Development of two novel face-recognition
CAPTCHAs: a security and usability study,” Computers & Security, vol.
60, no. July, pp. 95–116, 2016.'
mla: 'Schryen, Guido, et al. “Development of Two Novel Face-Recognition CAPTCHAs:
A Security and Usability Study.” Computers & Security, vol. 60, no.
July, Elsevier, 2016, pp. 95–116.'
short: G. Schryen, G. Wagner, A. Schlegel, Computers & Security 60 (2016) 95–116.
date_created: 2018-11-14T14:00:47Z
date_updated: 2022-01-06T07:02:10Z
ddc:
- '000'
department:
- _id: '277'
extern: '1'
file:
- access_level: open_access
content_type: application/pdf
creator: hsiemes
date_created: 2018-12-07T11:38:19Z
date_updated: 2018-12-13T15:07:36Z
file_id: '6029'
file_name: cose_991_final.pdf
file_size: 2983143
relation: main_file
file_date_updated: 2018-12-13T15:07:36Z
has_accepted_license: '1'
intvolume: ' 60'
issue: July
keyword:
- CAPTCHA
- Usability
- Facial features
- Gender classiffcation
- Age classification
- Face recognition reverse Turing test
language:
- iso: eng
oa: '1'
page: 95-116
publication: Computers & Security
publisher: Elsevier
status: public
title: 'Development of two novel face-recognition CAPTCHAs: a security and usability
study'
type: journal_article
user_id: '61579'
volume: 60
year: '2016'
...
---
_id: '11816'
abstract:
- lang: eng
text: In this paper, we consider the Maximum Likelihood (ML) estimation of the parameters
of a GAUSSIAN in the presence of censored, i.e., clipped data. We show that the
resulting Expectation Maximization (EM) algorithm delivers virtually biasfree
and efficient estimates, and we discuss its convergence properties. We also discuss
optimal classification in the presence of censored data. Censored data are frequently
encountered in wireless LAN positioning systems based on the fingerprinting method
employing signal strength measurements, due to the limited sensitivity of the
portable devices. Experiments both on simulated and real-world data demonstrate
the effectiveness of the proposed algorithms.
author:
- first_name: Manh Kha
full_name: Hoang, Manh Kha
last_name: Hoang
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Hoang MK, Haeb-Umbach R. Parameter estimation and classification of censored
Gaussian data with application to WiFi indoor positioning. In: 38th International
Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013). ; 2013:3721-3725.
doi:10.1109/ICASSP.2013.6638353'
apa: Hoang, M. K., & Haeb-Umbach, R. (2013). Parameter estimation and classification
of censored Gaussian data with application to WiFi indoor positioning. In 38th
International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)
(pp. 3721–3725). https://doi.org/10.1109/ICASSP.2013.6638353
bibtex: '@inproceedings{Hoang_Haeb-Umbach_2013, title={Parameter estimation and
classification of censored Gaussian data with application to WiFi indoor positioning},
DOI={10.1109/ICASSP.2013.6638353},
booktitle={38th International Conference on Acoustics, Speech, and Signal Processing
(ICASSP 2013)}, author={Hoang, Manh Kha and Haeb-Umbach, Reinhold}, year={2013},
pages={3721–3725} }'
chicago: Hoang, Manh Kha, and Reinhold Haeb-Umbach. “Parameter Estimation and Classification
of Censored Gaussian Data with Application to WiFi Indoor Positioning.” In 38th
International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013),
3721–25, 2013. https://doi.org/10.1109/ICASSP.2013.6638353.
ieee: M. K. Hoang and R. Haeb-Umbach, “Parameter estimation and classification of
censored Gaussian data with application to WiFi indoor positioning,” in 38th
International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013),
2013, pp. 3721–3725.
mla: Hoang, Manh Kha, and Reinhold Haeb-Umbach. “Parameter Estimation and Classification
of Censored Gaussian Data with Application to WiFi Indoor Positioning.” 38th
International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013),
2013, pp. 3721–25, doi:10.1109/ICASSP.2013.6638353.
short: 'M.K. Hoang, R. Haeb-Umbach, in: 38th International Conference on Acoustics,
Speech, and Signal Processing (ICASSP 2013), 2013, pp. 3721–3725.'
date_created: 2019-07-12T05:28:48Z
date_updated: 2022-01-06T06:51:09Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2013.6638353
keyword:
- Gaussian processes
- Global Positioning System
- convergence
- expectation-maximisation algorithm
- fingerprint identification
- indoor radio
- signal classification
- wireless LAN
- EM algorithm
- ML estimation
- WiFi indoor positioning
- censored Gaussian data classification
- clipped data
- convergence properties
- expectation maximization algorithm
- fingerprinting method
- maximum likelihood estimation
- optimal classification
- parameters estimation
- portable devices sensitivity
- signal strength measurements
- wireless LAN positioning systems
- Convergence
- IEEE 802.11 Standards
- Maximum likelihood estimation
- Parameter estimation
- Position measurement
- Training
- Indoor positioning
- censored data
- expectation maximization
- signal strength
- wireless LAN
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2013/HoHa2013.pdf
oa: '1'
page: 3721-3725
publication: 38th International Conference on Acoustics, Speech, and Signal Processing
(ICASSP 2013)
publication_identifier:
issn:
- 1520-6149
related_material:
link:
- description: Poster
relation: supplementary_material
url: https://groups.uni-paderborn.de/nt/pubs/2013/HoHa2013_Poster.pdf
status: public
title: Parameter estimation and classification of censored Gaussian data with application
to WiFi indoor positioning
type: conference
user_id: '44006'
year: '2013'
...
---
_id: '46388'
abstract:
- lang: eng
text: Understanding the behaviour of well-known algorithms for classical NP-hard
optimisation problems is still a difficult task. With this paper, we contribute
to this research direction and carry out a feature based comparison of local search
and the well-known Christofides approximation algorithm for the Traveling Salesperson
Problem. We use an evolutionary algorithm approach to construct easy and hard
instances for the Christofides algorithm, where we measure hardness in terms of
approximation ratio. Our results point out important features and lead to hard
and easy instances for this famous algorithm. Furthermore, our cross-comparison
gives new insights on the complementary benefits of the different approaches.
author:
- first_name: Samadhi
full_name: Nallaperuma, Samadhi
last_name: Nallaperuma
- first_name: Markus
full_name: Wagner, Markus
last_name: Wagner
- first_name: Frank
full_name: Neumann, Frank
last_name: Neumann
- first_name: Bernd
full_name: Bischl, Bernd
last_name: Bischl
- first_name: Olaf
full_name: Mersmann, Olaf
last_name: Mersmann
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Nallaperuma S, Wagner M, Neumann F, Bischl B, Mersmann O, Trautmann H. A Feature-Based
Comparison of Local Search and the Christofides Algorithm for the Travelling Salesperson
Problem. In: Proceedings of the Twelfth Workshop on Foundations of Genetic
Algorithms XII. FOGA XII ’13. Association for Computing Machinery; 2013:147–160.
doi:10.1145/2460239.2460253'
apa: Nallaperuma, S., Wagner, M., Neumann, F., Bischl, B., Mersmann, O., & Trautmann,
H. (2013). A Feature-Based Comparison of Local Search and the Christofides Algorithm
for the Travelling Salesperson Problem. Proceedings of the Twelfth Workshop
on Foundations of Genetic Algorithms XII, 147–160. https://doi.org/10.1145/2460239.2460253
bibtex: '@inproceedings{Nallaperuma_Wagner_Neumann_Bischl_Mersmann_Trautmann_2013,
place={New York, NY, USA}, series={FOGA XII ’13}, title={A Feature-Based Comparison
of Local Search and the Christofides Algorithm for the Travelling Salesperson
Problem}, DOI={10.1145/2460239.2460253},
booktitle={Proceedings of the Twelfth Workshop on Foundations of Genetic Algorithms
XII}, publisher={Association for Computing Machinery}, author={Nallaperuma, Samadhi
and Wagner, Markus and Neumann, Frank and Bischl, Bernd and Mersmann, Olaf and
Trautmann, Heike}, year={2013}, pages={147–160}, collection={FOGA XII ’13} }'
chicago: 'Nallaperuma, Samadhi, Markus Wagner, Frank Neumann, Bernd Bischl, Olaf
Mersmann, and Heike Trautmann. “A Feature-Based Comparison of Local Search and
the Christofides Algorithm for the Travelling Salesperson Problem.” In Proceedings
of the Twelfth Workshop on Foundations of Genetic Algorithms XII, 147–160.
FOGA XII ’13. New York, NY, USA: Association for Computing Machinery, 2013. https://doi.org/10.1145/2460239.2460253.'
ieee: 'S. Nallaperuma, M. Wagner, F. Neumann, B. Bischl, O. Mersmann, and H. Trautmann,
“A Feature-Based Comparison of Local Search and the Christofides Algorithm for
the Travelling Salesperson Problem,” in Proceedings of the Twelfth Workshop
on Foundations of Genetic Algorithms XII, 2013, pp. 147–160, doi: 10.1145/2460239.2460253.'
mla: Nallaperuma, Samadhi, et al. “A Feature-Based Comparison of Local Search and
the Christofides Algorithm for the Travelling Salesperson Problem.” Proceedings
of the Twelfth Workshop on Foundations of Genetic Algorithms XII, Association
for Computing Machinery, 2013, pp. 147–160, doi:10.1145/2460239.2460253.
short: 'S. Nallaperuma, M. Wagner, F. Neumann, B. Bischl, O. Mersmann, H. Trautmann,
in: Proceedings of the Twelfth Workshop on Foundations of Genetic Algorithms XII,
Association for Computing Machinery, New York, NY, USA, 2013, pp. 147–160.'
date_created: 2023-08-04T15:42:03Z
date_updated: 2023-10-16T13:45:53Z
department:
- _id: '34'
- _id: '819'
doi: 10.1145/2460239.2460253
keyword:
- approximation algorithms
- local search
- traveling salesperson problem
- feature selection
- prediction
- classification
language:
- iso: eng
page: 147–160
place: New York, NY, USA
publication: Proceedings of the Twelfth Workshop on Foundations of Genetic Algorithms
XII
publication_identifier:
isbn:
- '9781450319904'
publisher: Association for Computing Machinery
series_title: FOGA XII ’13
status: public
title: A Feature-Based Comparison of Local Search and the Christofides Algorithm for
the Travelling Salesperson Problem
type: conference
user_id: '15504'
year: '2013'
...
---
_id: '48889'
abstract:
- lang: eng
text: Meta-heuristics are frequently used to tackle NP-hard combinatorial optimization
problems. With this paper we contribute to the understanding of the success of
2-opt based local search algorithms for solving the traveling salesperson problem
(TSP). Although 2-opt is widely used in practice, it is hard to understand its
success from a theoretical perspective. We take a statistical approach and examine
the features of TSP instances that make the problem either hard or easy to solve.
As a measure of problem difficulty for 2-opt we use the approximation ratio that
it achieves on a given instance. Our investigations point out important features
that make TSP instances hard or easy to be approximated by 2-opt.
author:
- first_name: Olaf
full_name: Mersmann, Olaf
last_name: Mersmann
- first_name: Bernd
full_name: Bischl, Bernd
last_name: Bischl
- first_name: Heike
full_name: Trautmann, Heike
last_name: Trautmann
- first_name: Markus
full_name: Wagner, Markus
last_name: Wagner
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Frank
full_name: Neumann, Frank
last_name: Neumann
citation:
ama: Mersmann O, Bischl B, Trautmann H, Wagner M, Bossek J, Neumann F. A Novel Feature-Based
Approach to Characterize Algorithm Performance for the Traveling Salesperson Problem.
Annals of Mathematics and Artificial Intelligence. 2013;69(2):151–182.
doi:10.1007/s10472-013-9341-2
apa: Mersmann, O., Bischl, B., Trautmann, H., Wagner, M., Bossek, J., & Neumann,
F. (2013). A Novel Feature-Based Approach to Characterize Algorithm Performance
for the Traveling Salesperson Problem. Annals of Mathematics and Artificial
Intelligence, 69(2), 151–182. https://doi.org/10.1007/s10472-013-9341-2
bibtex: '@article{Mersmann_Bischl_Trautmann_Wagner_Bossek_Neumann_2013, title={A
Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling
Salesperson Problem}, volume={69}, DOI={10.1007/s10472-013-9341-2},
number={2}, journal={Annals of Mathematics and Artificial Intelligence}, author={Mersmann,
Olaf and Bischl, Bernd and Trautmann, Heike and Wagner, Markus and Bossek, Jakob
and Neumann, Frank}, year={2013}, pages={151–182} }'
chicago: 'Mersmann, Olaf, Bernd Bischl, Heike Trautmann, Markus Wagner, Jakob Bossek,
and Frank Neumann. “A Novel Feature-Based Approach to Characterize Algorithm Performance
for the Traveling Salesperson Problem.” Annals of Mathematics and Artificial
Intelligence 69, no. 2 (2013): 151–182. https://doi.org/10.1007/s10472-013-9341-2.'
ieee: 'O. Mersmann, B. Bischl, H. Trautmann, M. Wagner, J. Bossek, and F. Neumann,
“A Novel Feature-Based Approach to Characterize Algorithm Performance for the
Traveling Salesperson Problem,” Annals of Mathematics and Artificial Intelligence,
vol. 69, no. 2, pp. 151–182, 2013, doi: 10.1007/s10472-013-9341-2.'
mla: Mersmann, Olaf, et al. “A Novel Feature-Based Approach to Characterize Algorithm
Performance for the Traveling Salesperson Problem.” Annals of Mathematics and
Artificial Intelligence, vol. 69, no. 2, 2013, pp. 151–182, doi:10.1007/s10472-013-9341-2.
short: O. Mersmann, B. Bischl, H. Trautmann, M. Wagner, J. Bossek, F. Neumann, Annals
of Mathematics and Artificial Intelligence 69 (2013) 151–182.
date_created: 2023-11-14T15:58:59Z
date_updated: 2023-12-13T10:50:41Z
department:
- _id: '819'
doi: 10.1007/s10472-013-9341-2
intvolume: ' 69'
issue: '2'
keyword:
- 2-opt
- 90B06
- Classification
- Feature selection
- MARS
- TSP
language:
- iso: eng
page: 151–182
publication: Annals of Mathematics and Artificial Intelligence
publication_identifier:
issn:
- 1012-2443
status: public
title: A Novel Feature-Based Approach to Characterize Algorithm Performance for the
Traveling Salesperson Problem
type: journal_article
user_id: '102979'
volume: 69
year: '2013'
...
---
_id: '48890'
abstract:
- lang: eng
text: With this paper we contribute to the understanding of the success of 2-opt
based local search algorithms for solving the traveling salesman problem TSP.
Although 2-opt is widely used in practice, it is hard to understand its success
from a theoretical perspective. We take a statistical approach and examine the
features of TSP instances that make the problem either hard or easy to solve.
As a measure of problem difficulty for 2-opt we use the approximation ratio that
it achieves on a given instance. Our investigations point out important features
that make TSP instances hard or easy to be approximated by 2-opt.
author:
- first_name: Olaf
full_name: Mersmann, Olaf
last_name: Mersmann
- first_name: Bernd
full_name: Bischl, Bernd
last_name: Bischl
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Heike
full_name: Trautmann, Heike
last_name: Trautmann
- first_name: Markus
full_name: Wagner, Markus
last_name: Wagner
- first_name: Frank
full_name: Neumann, Frank
last_name: Neumann
citation:
ama: 'Mersmann O, Bischl B, Bossek J, Trautmann H, Wagner M, Neumann F. Local Search
and the Traveling Salesman Problem: A Feature-Based Characterization of Problem
Hardness. In: Revised Selected Papers of the 6th International Conference on
Learning and Intelligent Optimization - Volume 7219. LION 6. Springer-Verlag;
2012:115–129.'
apa: 'Mersmann, O., Bischl, B., Bossek, J., Trautmann, H., Wagner, M., & Neumann,
F. (2012). Local Search and the Traveling Salesman Problem: A Feature-Based Characterization
of Problem Hardness. Revised Selected Papers of the 6th International Conference
on Learning and Intelligent Optimization - Volume 7219, 115–129.'
bibtex: '@inproceedings{Mersmann_Bischl_Bossek_Trautmann_Wagner_Neumann_2012, place={Berlin,
Heidelberg}, series={LION 6}, title={Local Search and the Traveling Salesman Problem:
A Feature-Based Characterization of Problem Hardness}, booktitle={Revised Selected
Papers of the 6th International Conference on Learning and Intelligent Optimization
- Volume 7219}, publisher={Springer-Verlag}, author={Mersmann, Olaf and Bischl,
Bernd and Bossek, Jakob and Trautmann, Heike and Wagner, Markus and Neumann, Frank},
year={2012}, pages={115–129}, collection={LION 6} }'
chicago: 'Mersmann, Olaf, Bernd Bischl, Jakob Bossek, Heike Trautmann, Markus Wagner,
and Frank Neumann. “Local Search and the Traveling Salesman Problem: A Feature-Based
Characterization of Problem Hardness.” In Revised Selected Papers of the 6th
International Conference on Learning and Intelligent Optimization - Volume 7219,
115–129. LION 6. Berlin, Heidelberg: Springer-Verlag, 2012.'
ieee: 'O. Mersmann, B. Bischl, J. Bossek, H. Trautmann, M. Wagner, and F. Neumann,
“Local Search and the Traveling Salesman Problem: A Feature-Based Characterization
of Problem Hardness,” in Revised Selected Papers of the 6th International Conference
on Learning and Intelligent Optimization - Volume 7219, 2012, pp. 115–129.'
mla: 'Mersmann, Olaf, et al. “Local Search and the Traveling Salesman Problem: A
Feature-Based Characterization of Problem Hardness.” Revised Selected Papers
of the 6th International Conference on Learning and Intelligent Optimization -
Volume 7219, Springer-Verlag, 2012, pp. 115–129.'
short: 'O. Mersmann, B. Bischl, J. Bossek, H. Trautmann, M. Wagner, F. Neumann,
in: Revised Selected Papers of the 6th International Conference on Learning and
Intelligent Optimization - Volume 7219, Springer-Verlag, Berlin, Heidelberg, 2012,
pp. 115–129.'
date_created: 2023-11-14T15:58:59Z
date_updated: 2023-12-13T10:48:58Z
department:
- _id: '819'
extern: '1'
keyword:
- 2-opt
- Classification
- Feature Selection
- MARS
- TSP
language:
- iso: eng
page: 115–129
place: Berlin, Heidelberg
publication: Revised Selected Papers of the 6th International Conference on Learning
and Intelligent Optimization - Volume 7219
publication_identifier:
isbn:
- 978-3-642-34412-1
publisher: Springer-Verlag
series_title: LION 6
status: public
title: 'Local Search and the Traveling Salesman Problem: A Feature-Based Characterization
of Problem Hardness'
type: conference
user_id: '102979'
year: '2012'
...
---
_id: '1122'
abstract:
- lang: eng
text: Within this paper, we will describe a new approach to customer interaction
management by integrating social networking channels into existing business processes.
Until now, contact center agents still read these messages and forward them to
the persons in charge of customer’s in the company. But with the introduction
of Web 2.0 and social networking clients are more likely to communicate with the
companies via Facebook and Twitter instead of filling data in contact forms or
sending e-mail requests. In order to maintain an active communication with international
clients via social media, the multilingual consumer contacts have to be categorized
and then automatically assigned to the corresponding business processes (e.g.
technicalservice, shipping, marketing, and accounting). This allows the company
to follow general trends in customer opinions on the Internet, but also record
two-sided communication for customer relationship management.
author:
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
- first_name: Yeong Su
full_name: Lee, Yeong Su
last_name: Lee
- first_name: Matthias
full_name: Bargel, Matthias
last_name: Bargel
citation:
ama: 'Geierhos M, Lee YS, Bargel M. Processing Multilingual Customer Contacts via
Social Media. In: Hedeland H, Schmidt T, Wörner K, eds. Multilingual Resources,
Multilingual Applications: Proceedings of the Conference of the German Society
for Computational Linguistics and Language Technology (GSCL) 2011. Vol 96.
Arbeiten zur Mehrsprachigkeit - Folge B. Hamburg, Germany: University of Hamburg;
2011:219-222.'
apa: 'Geierhos, M., Lee, Y. S., & Bargel, M. (2011). Processing Multilingual
Customer Contacts via Social Media. In H. Hedeland, T. Schmidt, & K. Wörner
(Eds.), Multilingual Resources, Multilingual Applications: Proceedings of the
Conference of the German Society for Computational Linguistics and Language Technology
(GSCL) 2011 (Vol. 96, pp. 219–222). Hamburg, Germany: University of Hamburg.'
bibtex: '@inproceedings{Geierhos_Lee_Bargel_2011, place={Hamburg, Germany}, series={Arbeiten
zur Mehrsprachigkeit - Folge B}, title={Processing Multilingual Customer Contacts
via Social Media}, volume={96}, booktitle={Multilingual Resources, Multilingual
Applications: Proceedings of the Conference of the German Society for Computational
Linguistics and Language Technology (GSCL) 2011}, publisher={University of Hamburg},
author={Geierhos, Michaela and Lee, Yeong Su and Bargel, Matthias}, editor={Hedeland,
Hanna and Schmidt, Thomas and Wörner, KaiEditors}, year={2011}, pages={219–222},
collection={Arbeiten zur Mehrsprachigkeit - Folge B} }'
chicago: 'Geierhos, Michaela, Yeong Su Lee, and Matthias Bargel. “Processing Multilingual
Customer Contacts via Social Media.” In Multilingual Resources, Multilingual
Applications: Proceedings of the Conference of the German Society for Computational
Linguistics and Language Technology (GSCL) 2011, edited by Hanna Hedeland,
Thomas Schmidt, and Kai Wörner, 96:219–22. Arbeiten Zur Mehrsprachigkeit - Folge
B. Hamburg, Germany: University of Hamburg, 2011.'
ieee: 'M. Geierhos, Y. S. Lee, and M. Bargel, “Processing Multilingual Customer
Contacts via Social Media,” in Multilingual Resources, Multilingual Applications:
Proceedings of the Conference of the German Society for Computational Linguistics
and Language Technology (GSCL) 2011, Hamburg, Germany, 2011, vol. 96, pp.
219–222.'
mla: 'Geierhos, Michaela, et al. “Processing Multilingual Customer Contacts via
Social Media.” Multilingual Resources, Multilingual Applications: Proceedings
of the Conference of the German Society for Computational Linguistics and Language
Technology (GSCL) 2011, edited by Hanna Hedeland et al., vol. 96, University
of Hamburg, 2011, pp. 219–22.'
short: 'M. Geierhos, Y.S. Lee, M. Bargel, in: H. Hedeland, T. Schmidt, K. Wörner
(Eds.), Multilingual Resources, Multilingual Applications: Proceedings of the
Conference of the German Society for Computational Linguistics and Language Technology
(GSCL) 2011, University of Hamburg, Hamburg, Germany, 2011, pp. 219–222.'
conference:
end_date: 2011-09-30
location: Hamburg, Germany
name: Conference of the German Society for Computational Linguistics and Language
Technology (GSCL 2011)
start_date: 2011-09-28
date_created: 2018-01-29T15:48:34Z
date_updated: 2022-01-06T06:50:58Z
department:
- _id: '36'
- _id: '1'
- _id: '579'
editor:
- first_name: Hanna
full_name: Hedeland, Hanna
last_name: Hedeland
- first_name: Thomas
full_name: Schmidt, Thomas
last_name: Schmidt
- first_name: Kai
full_name: Wörner, Kai
last_name: Wörner
extern: '1'
intvolume: ' 96'
keyword:
- Classification of Multilingual Customer Contacts
- Contact Center Application Support
- Social Media Business Integration
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://exmaralda.org/gscl2011/downloads/AZM96.pdf
oa: '1'
page: 219-222
place: Hamburg, Germany
publication: 'Multilingual Resources, Multilingual Applications: Proceedings of the
Conference of the German Society for Computational Linguistics and Language Technology
(GSCL) 2011'
publication_identifier:
issn:
- 0176-599X
publication_status: published
publisher: University of Hamburg
quality_controlled: '1'
series_title: Arbeiten zur Mehrsprachigkeit - Folge B
status: public
title: Processing Multilingual Customer Contacts via Social Media
type: conference
user_id: '42496'
volume: 96
year: '2011'
...
---
_id: '9763'
abstract:
- lang: eng
text: Recent advances in information processing enable new kinds of technical systems,
called self-optimizing systems. These systems are able to adapt their objectives
and their behavior according to the current situation and influences autonomously.
This behavior adaptation is non-deterministic and hence self-optimization is a
risk to the system, e.g. if the result of the self-optimization process does not
match the suddenly changed situation. In contrary, self-optimization could be
used to increase the dependability by pursuing objectives like reliability and
availability. In our preceding publications we introduced the so called multi-level
dependability concept to cope with this new kind of systems (cf. [6]). This concept
comprises the monitoring of the system behavior, the classification of the current
situation, and the selection of the appropriate measure, if reliability limits
are exceeded. In this paper we present for the first time experimental results.
The dependability concept is implemented in the self-optimizing active guidance
system of a railway vehicle. The test drives illustrate clearly that the proposed
concept is able to cope with, e.g., sensor failures, and is able to increase the
reliability and availability of the active guidance module.
author:
- first_name: Christoph
full_name: Sondermann-Wölke, Christoph
last_name: Sondermann-Wölke
- first_name: Jens
full_name: Geisler, Jens
last_name: Geisler
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: 'Sondermann-Wölke C, Geisler J, Sextro W. Increasing the reliability of a self-optimizing
railway guidance system. In: Reliability and Maintainability Symposium (RAMS),
2010 Proceedings - Annual. ; 2010:1-6. doi:10.1109/RAMS.2010.5448080'
apa: Sondermann-Wölke, C., Geisler, J., & Sextro, W. (2010). Increasing the
reliability of a self-optimizing railway guidance system. In Reliability and
Maintainability Symposium (RAMS), 2010 Proceedings - Annual (pp. 1–6). https://doi.org/10.1109/RAMS.2010.5448080
bibtex: '@inproceedings{Sondermann-Wölke_Geisler_Sextro_2010, title={Increasing
the reliability of a self-optimizing railway guidance system}, DOI={10.1109/RAMS.2010.5448080},
booktitle={Reliability and Maintainability Symposium (RAMS), 2010 Proceedings
- Annual}, author={Sondermann-Wölke, Christoph and Geisler, Jens and Sextro, Walter},
year={2010}, pages={1–6} }'
chicago: Sondermann-Wölke, Christoph, Jens Geisler, and Walter Sextro. “Increasing
the Reliability of a Self-Optimizing Railway Guidance System.” In Reliability
and Maintainability Symposium (RAMS), 2010 Proceedings - Annual, 1–6, 2010.
https://doi.org/10.1109/RAMS.2010.5448080.
ieee: C. Sondermann-Wölke, J. Geisler, and W. Sextro, “Increasing the reliability
of a self-optimizing railway guidance system,” in Reliability and Maintainability
Symposium (RAMS), 2010 Proceedings - Annual, 2010, pp. 1–6.
mla: Sondermann-Wölke, Christoph, et al. “Increasing the Reliability of a Self-Optimizing
Railway Guidance System.” Reliability and Maintainability Symposium (RAMS),
2010 Proceedings - Annual, 2010, pp. 1–6, doi:10.1109/RAMS.2010.5448080.
short: 'C. Sondermann-Wölke, J. Geisler, W. Sextro, in: Reliability and Maintainability
Symposium (RAMS), 2010 Proceedings - Annual, 2010, pp. 1–6.'
date_created: 2019-05-13T10:35:39Z
date_updated: 2022-01-06T07:04:19Z
department:
- _id: '151'
doi: 10.1109/RAMS.2010.5448080
keyword:
- availability
- dependability concept
- multilevel dependability concept
- railway vehicle
- reliability
- self optimizing active guidance system
- self optimizing railway guidance system
- situation classification
- system behavior monitoring
- optimal control
- railways
- reliability theory
- self-adjusting systems
language:
- iso: eng
page: 1 -6
publication: Reliability and Maintainability Symposium (RAMS), 2010 Proceedings -
Annual
publication_identifier:
issn:
- 0149-144X
quality_controlled: '1'
status: public
title: Increasing the reliability of a self-optimizing railway guidance system
type: conference
user_id: '55222'
year: '2010'
...
---
_id: '37037'
abstract:
- lang: eng
text: Today we can identify a big gap between requirement specification and the
generation of test environments. This article extends the Classification Tree
Method for Embedded Systems (CTM/ES) to fill this gap by new concepts for the
precise specification of stimuli for operational ranges of continuous control
systems. It introduces novel means for continuous acceptance criteria definition
and for functional coverage definition.
author:
- first_name: Alexander
full_name: Krupp, Alexander
last_name: Krupp
- first_name: Wolfgang
full_name: Müller, Wolfgang
id: '16243'
last_name: Müller
citation:
ama: 'Krupp A, Müller W. A Systematic Approach to Combined HW/SW System Test. In:
Proceedings of DATE’10. IEEE; 2010. doi:10.1109/DATE.2010.5457186'
apa: Krupp, A., & Müller, W. (2010). A Systematic Approach to Combined HW/SW
System Test. Proceedings of DATE’10. Design, Automation & Test in Europe
Conference & Exhibition (DATE 2010), Dresden. https://doi.org/10.1109/DATE.2010.5457186
bibtex: '@inproceedings{Krupp_Müller_2010, place={Dresden}, title={A Systematic
Approach to Combined HW/SW System Test}, DOI={10.1109/DATE.2010.5457186},
booktitle={Proceedings of DATE’10}, publisher={IEEE}, author={Krupp, Alexander
and Müller, Wolfgang}, year={2010} }'
chicago: 'Krupp, Alexander, and Wolfgang Müller. “A Systematic Approach to Combined
HW/SW System Test.” In Proceedings of DATE’10. Dresden: IEEE, 2010. https://doi.org/10.1109/DATE.2010.5457186.'
ieee: 'A. Krupp and W. Müller, “A Systematic Approach to Combined HW/SW System Test,”
presented at the Design, Automation & Test in Europe Conference & Exhibition
(DATE 2010), Dresden, 2010, doi: 10.1109/DATE.2010.5457186.'
mla: Krupp, Alexander, and Wolfgang Müller. “A Systematic Approach to Combined HW/SW
System Test.” Proceedings of DATE’10, IEEE, 2010, doi:10.1109/DATE.2010.5457186.
short: 'A. Krupp, W. Müller, in: Proceedings of DATE’10, IEEE, Dresden, 2010.'
conference:
location: Dresden
name: Design, Automation & Test in Europe Conference & Exhibition (DATE 2010)
date_created: 2023-01-17T10:41:15Z
date_updated: 2023-01-17T10:41:25Z
department:
- _id: '672'
doi: 10.1109/DATE.2010.5457186
keyword:
- System testing
- Automatic testing
- Object oriented modeling
- Classification tree analysis
- Automotive engineering
- Mathematical model
- Embedded system
- Control systems
- Electronic equipment testing
- Software testing
language:
- iso: eng
place: Dresden
publication: Proceedings of DATE’10
publisher: IEEE
status: public
title: A Systematic Approach to Combined HW/SW System Test
type: conference
user_id: '5786'
year: '2010'
...