---
_id: '32591'
author:
- first_name: Cedric
full_name: Richter, Cedric
id: '50003'
last_name: Richter
- first_name: Heike
full_name: Wehrheim, Heike
id: '573'
last_name: Wehrheim
citation:
ama: 'Richter C, Wehrheim H. TSSB-3M: Mining single statement bugs at massive scale.
In: 2022 IEEE/ACM 19th International Conference on Mining Software Repositories
(MSR). ; 2022:418-422. doi:10.1145/3524842.3528505'
apa: 'Richter, C., & Wehrheim, H. (2022). TSSB-3M: Mining single statement bugs
at massive scale. 2022 IEEE/ACM 19th International Conference on Mining Software
Repositories (MSR), 418–422. https://doi.org/10.1145/3524842.3528505'
bibtex: '@inproceedings{Richter_Wehrheim_2022, title={TSSB-3M: Mining single statement
bugs at massive scale}, DOI={10.1145/3524842.3528505},
booktitle={2022 IEEE/ACM 19th International Conference on Mining Software Repositories
(MSR)}, author={Richter, Cedric and Wehrheim, Heike}, year={2022}, pages={418–422}
}'
chicago: 'Richter, Cedric, and Heike Wehrheim. “TSSB-3M: Mining Single Statement
Bugs at Massive Scale.” In 2022 IEEE/ACM 19th International Conference on Mining
Software Repositories (MSR), 418–22, 2022. https://doi.org/10.1145/3524842.3528505.'
ieee: 'C. Richter and H. Wehrheim, “TSSB-3M: Mining single statement bugs at massive
scale,” in 2022 IEEE/ACM 19th International Conference on Mining Software Repositories
(MSR), 2022, pp. 418–422, doi: 10.1145/3524842.3528505.'
mla: 'Richter, Cedric, and Heike Wehrheim. “TSSB-3M: Mining Single Statement Bugs
at Massive Scale.” 2022 IEEE/ACM 19th International Conference on Mining Software
Repositories (MSR), 2022, pp. 418–22, doi:10.1145/3524842.3528505.'
short: 'C. Richter, H. Wehrheim, in: 2022 IEEE/ACM 19th International Conference
on Mining Software Repositories (MSR), 2022, pp. 418–422.'
date_created: 2022-08-08T07:42:19Z
date_updated: 2022-11-18T09:45:05Z
department:
- _id: '77'
doi: 10.1145/3524842.3528505
language:
- iso: eng
page: 418-422
project:
- _id: '12'
name: 'SFB 901 - B4: SFB 901 - Subproject B4'
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
publication: 2022 IEEE/ACM 19th International Conference on Mining Software Repositories
(MSR)
status: public
title: 'TSSB-3M: Mining single statement bugs at massive scale'
type: conference
user_id: '477'
year: '2022'
...
---
_id: '31806'
abstract:
- lang: eng
text: The creation of an RDF knowledge graph for a particular application commonly
involves a pipeline of tools that transform a set ofinput data sources into an
RDF knowledge graph in a process called dataset augmentation. The components of
such augmentation pipelines often require extensive configuration to lead to satisfactory
results. Thus, non-experts are often unable to use them. Wepresent an efficient
supervised algorithm based on genetic programming for learning knowledge graph
augmentation pipelines of arbitrary length. Our approach uses multi-expression
learning to learn augmentation pipelines able to achieve a high F-measure on the
training data. Our evaluation suggests that our approach can efficiently learn
a larger class of RDF dataset augmentation tasks than the state of the art while
using only a single training example. Even on the most complex augmentation problem
we posed, our approach consistently achieves an average F1-measure of 99% in under
500 iterations with an average runtime of 16 seconds
author:
- first_name: Kevin
full_name: Dreßler, Kevin
id: '78256'
last_name: Dreßler
- first_name: Mohamed
full_name: Sherif, Mohamed
id: '67234'
last_name: Sherif
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Dreßler K, Sherif M, Ngonga Ngomo A-C. ADAGIO - Automated Data Augmentation
of Knowledge Graphs Using Multi-expression Learning. In: Proceedings of the
33rd ACM Conference on Hypertext and Hypermedia. ; 2022. doi:10.1145/3511095.3531287'
apa: 'Dreßler, K., Sherif, M., & Ngonga Ngomo, A.-C. (2022). ADAGIO - Automated
Data Augmentation of Knowledge Graphs Using Multi-expression Learning. Proceedings
of the 33rd ACM Conference on Hypertext and Hypermedia. HT ’22: 33rd ACM Conference
on Hypertext and Social Media, Barcelona (Spain). https://doi.org/10.1145/3511095.3531287'
bibtex: '@inproceedings{Dreßler_Sherif_Ngonga Ngomo_2022, title={ADAGIO - Automated
Data Augmentation of Knowledge Graphs Using Multi-expression Learning}, DOI={10.1145/3511095.3531287}, booktitle={Proceedings
of the 33rd ACM Conference on Hypertext and Hypermedia}, author={Dreßler, Kevin
and Sherif, Mohamed and Ngonga Ngomo, Axel-Cyrille}, year={2022} }'
chicago: Dreßler, Kevin, Mohamed Sherif, and Axel-Cyrille Ngonga Ngomo. “ADAGIO
- Automated Data Augmentation of Knowledge Graphs Using Multi-Expression Learning.”
In Proceedings of the 33rd ACM Conference on Hypertext and Hypermedia,
2022. https://doi.org/10.1145/3511095.3531287.
ieee: 'K. Dreßler, M. Sherif, and A.-C. Ngonga Ngomo, “ADAGIO - Automated Data Augmentation
of Knowledge Graphs Using Multi-expression Learning,” presented at the HT ’22:
33rd ACM Conference on Hypertext and Social Media, Barcelona (Spain), 2022, doi:
10.1145/3511095.3531287.'
mla: Dreßler, Kevin, et al. “ADAGIO - Automated Data Augmentation of Knowledge Graphs
Using Multi-Expression Learning.” Proceedings of the 33rd ACM Conference on
Hypertext and Hypermedia, 2022, doi:10.1145/3511095.3531287.
short: 'K. Dreßler, M. Sherif, A.-C. Ngonga Ngomo, in: Proceedings of the 33rd ACM
Conference on Hypertext and Hypermedia, 2022.'
conference:
end_date: 2022-07-01
location: Barcelona (Spain)
name: 'HT ’22: 33rd ACM Conference on Hypertext and Social Media'
start_date: 2022-06-28
date_created: 2022-06-08T08:47:33Z
date_updated: 2022-11-18T10:11:38Z
ddc:
- '000'
department:
- _id: '34'
doi: 10.1145/3511095.3531287
keyword:
- 2022 RAKI SFB901 deer dice kevin knowgraphs limes ngonga sherif simba
language:
- iso: eng
project:
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '10'
name: 'SFB 901 - B2: SFB 901 - Subproject B2'
publication: Proceedings of the 33rd ACM Conference on Hypertext and Hypermedia
status: public
title: ADAGIO - Automated Data Augmentation of Knowledge Graphs Using Multi-expression
Learning
type: conference
user_id: '477'
year: '2022'
...
---
_id: '33274'
author:
- first_name: Wei-Fan
full_name: Chen, Wei-Fan
id: '82920'
last_name: Chen
- first_name: Mei-Hua
full_name: Chen, Mei-Hua
last_name: Chen
- first_name: Garima
full_name: Mudgal, Garima
last_name: Mudgal
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: 'Chen W-F, Chen M-H, Mudgal G, Wachsmuth H. Analyzing Culture-Specific Argument
Structures in Learner Essays. In: Proceedings of the 9th Workshop on Argument
Mining (ArgMining 2022). ; 2022:51-61.'
apa: Chen, W.-F., Chen, M.-H., Mudgal, G., & Wachsmuth, H. (2022). Analyzing
Culture-Specific Argument Structures in Learner Essays. Proceedings of the
9th Workshop on Argument Mining (ArgMining 2022), 51–61.
bibtex: '@inproceedings{Chen_Chen_Mudgal_Wachsmuth_2022, title={Analyzing Culture-Specific
Argument Structures in Learner Essays}, booktitle={Proceedings of the 9th Workshop
on Argument Mining (ArgMining 2022)}, author={Chen, Wei-Fan and Chen, Mei-Hua
and Mudgal, Garima and Wachsmuth, Henning}, year={2022}, pages={51–61} }'
chicago: Chen, Wei-Fan, Mei-Hua Chen, Garima Mudgal, and Henning Wachsmuth. “Analyzing
Culture-Specific Argument Structures in Learner Essays.” In Proceedings of
the 9th Workshop on Argument Mining (ArgMining 2022), 51–61, 2022.
ieee: W.-F. Chen, M.-H. Chen, G. Mudgal, and H. Wachsmuth, “Analyzing Culture-Specific
Argument Structures in Learner Essays,” in Proceedings of the 9th Workshop
on Argument Mining (ArgMining 2022), 2022, pp. 51–61.
mla: Chen, Wei-Fan, et al. “Analyzing Culture-Specific Argument Structures in Learner
Essays.” Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022),
2022, pp. 51–61.
short: 'W.-F. Chen, M.-H. Chen, G. Mudgal, H. Wachsmuth, in: Proceedings of the
9th Workshop on Argument Mining (ArgMining 2022), 2022, pp. 51–61.'
date_created: 2022-09-06T13:51:23Z
date_updated: 2022-11-18T09:56:17Z
department:
- _id: '600'
language:
- iso: eng
page: 51 - 61
project:
- _id: '9'
name: 'SFB 901 - B1: SFB 901 - Subproject B1'
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
publication: Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022)
status: public
title: Analyzing Culture-Specific Argument Structures in Learner Essays
type: conference
user_id: '477'
year: '2022'
...
---
_id: '32179'
abstract:
- lang: eng
text: This work addresses the automatic resolution of software requirements. In
the vision of On-The-Fly Computing, software services should be composed on demand,
based solely on natural language input from human users. To enable this, we build
a chatbot solution that works with human-in-the-loop support to receive, analyze,
correct, and complete their software requirements. The chatbot is equipped with
a natural language processing pipeline and a large knowledge base, as well as
sophisticated dialogue management skills to enhance the user experience. Previous
solutions have focused on analyzing software requirements to point out errors
such as vagueness, ambiguity, or incompleteness. Our work shows how apps can collaborate
with users to efficiently produce correct requirements. We developed and compared
three different chatbot apps that can work with built-in knowledge. We rely on
ChatterBot, DialoGPT and Rasa for this purpose. While DialoGPT provides its own
knowledge base, Rasa is the best system to combine the text mining and knowledge
solutions at our disposal. The evaluation shows that users accept 73% of the suggested
answers from Rasa, while they accept only 63% from DialoGPT or even 36% from ChatterBot.
author:
- first_name: Joschka
full_name: Kersting, Joschka
id: '58701'
last_name: Kersting
- first_name: Mobeen
full_name: Ahmed, Mobeen
last_name: Ahmed
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
citation:
ama: 'Kersting J, Ahmed M, Geierhos M. Chatbot-Enhanced Requirements Resolution
for Automated Service Compositions. In: Stephanidis C, Antona M, Ntoa S, eds.
HCI International 2022 Posters. Vol 1580. Communications in Computer and
Information Science (CCIS). Springer International Publishing; 2022:419--426.
doi:10.1007/978-3-031-06417-3_56'
apa: Kersting, J., Ahmed, M., & Geierhos, M. (2022). Chatbot-Enhanced Requirements
Resolution for Automated Service Compositions. In C. Stephanidis, M. Antona, &
S. Ntoa (Eds.), HCI International 2022 Posters (Vol. 1580, pp. 419--426).
Springer International Publishing. https://doi.org/10.1007/978-3-031-06417-3_56
bibtex: '@inbook{Kersting_Ahmed_Geierhos_2022, place={Cham, Switzerland}, series={Communications
in Computer and Information Science (CCIS)}, title={Chatbot-Enhanced Requirements
Resolution for Automated Service Compositions}, volume={1580}, DOI={10.1007/978-3-031-06417-3_56},
booktitle={HCI International 2022 Posters}, publisher={Springer International
Publishing}, author={Kersting, Joschka and Ahmed, Mobeen and Geierhos, Michaela},
editor={Stephanidis, Constantine and Antona, Margherita and Ntoa, Stavroula},
year={2022}, pages={419--426}, collection={Communications in Computer and Information
Science (CCIS)} }'
chicago: 'Kersting, Joschka, Mobeen Ahmed, and Michaela Geierhos. “Chatbot-Enhanced
Requirements Resolution for Automated Service Compositions.” In HCI International
2022 Posters, edited by Constantine Stephanidis, Margherita Antona, and Stavroula
Ntoa, 1580:419--426. Communications in Computer and Information Science (CCIS).
Cham, Switzerland: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-031-06417-3_56.'
ieee: 'J. Kersting, M. Ahmed, and M. Geierhos, “Chatbot-Enhanced Requirements Resolution
for Automated Service Compositions,” in HCI International 2022 Posters,
vol. 1580, C. Stephanidis, M. Antona, and S. Ntoa, Eds. Cham, Switzerland: Springer
International Publishing, 2022, pp. 419--426.'
mla: Kersting, Joschka, et al. “Chatbot-Enhanced Requirements Resolution for Automated
Service Compositions.” HCI International 2022 Posters, edited by Constantine
Stephanidis et al., vol. 1580, Springer International Publishing, 2022, pp. 419--426,
doi:10.1007/978-3-031-06417-3_56.
short: 'J. Kersting, M. Ahmed, M. Geierhos, in: C. Stephanidis, M. Antona, S. Ntoa
(Eds.), HCI International 2022 Posters, Springer International Publishing, Cham,
Switzerland, 2022, pp. 419--426.'
conference:
end_date: 2022-07-01
location: Virtual
name: 24th International Conference on Human-Computer Interaction (HCII 2022)
start_date: 2022-06-26
date_created: 2022-06-27T09:27:06Z
date_updated: 2022-11-28T13:22:16Z
ddc:
- '004'
department:
- _id: '579'
doi: 10.1007/978-3-031-06417-3_56
editor:
- first_name: Constantine
full_name: Stephanidis, Constantine
last_name: Stephanidis
- first_name: Margherita
full_name: Antona, Margherita
last_name: Antona
- first_name: Stavroula
full_name: Ntoa, Stavroula
last_name: Ntoa
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2022-11-28T13:21:32Z
date_updated: 2022-11-28T13:21:32Z
file_id: '34150'
file_name: Kersting et al. (2022), Kersting2022.pdf
file_size: 1153017
relation: main_file
success: 1
file_date_updated: 2022-11-28T13:21:32Z
has_accepted_license: '1'
intvolume: ' 1580'
keyword:
- On-The-Fly Computing
- Chatbot
- Knowledge Base
language:
- iso: eng
page: 419--426
place: Cham, Switzerland
project:
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '9'
name: 'SFB 901 - B1: SFB 901 - Subproject B1'
publication: HCI International 2022 Posters
publication_identifier:
isbn:
- '9783031064166'
- '9783031064173'
issn:
- 1865-0929
- 1865-0937
publication_status: published
publisher: Springer International Publishing
related_material:
link:
- relation: confirmation
url: https://link.springer.com/chapter/10.1007/978-3-031-06417-3_56
series_title: Communications in Computer and Information Science (CCIS)
status: public
title: Chatbot-Enhanced Requirements Resolution for Automated Service Compositions
type: book_chapter
user_id: '58701'
volume: 1580
year: '2022'
...
---
_id: '31054'
abstract:
- lang: eng
text: This paper aims at discussing past limitations set in sentiment analysis research
regarding explicit and implicit mentions of opinions. Previous studies have regularly
neglected this question in favor of methodical research on standard-datasets.
Furthermore, they were limited to linguistically less-diverse domains, such as
commercial product reviews. We face this issue by annotating a German-language
physician review dataset that contains numerous implicit, long, and complex statements
that indicate aspect ratings, such as the physician’s friendliness. We discuss
the nature of implicit statements and present various samples to illustrate the
challenge described.
author:
- first_name: Joschka
full_name: Kersting, Joschka
id: '58701'
last_name: Kersting
- first_name: Frederik Simon
full_name: Bäumer, Frederik Simon
id: '38837'
last_name: Bäumer
citation:
ama: 'Kersting J, Bäumer FS. Implicit Statements in Healthcare Reviews: A Challenge
for Sentiment Analysis. In: Kersting J, ed. Proceedings of the Fourteenth International
Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track
AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications.
IARIA; 2022:5-9.'
apa: 'Kersting, J., & Bäumer, F. S. (2022). Implicit Statements in Healthcare
Reviews: A Challenge for Sentiment Analysis. In J. Kersting (Ed.), Proceedings
of the Fourteenth International Conference on Pervasive Patterns and Applications
(PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data
Science for Real-World Applications (pp. 5–9). IARIA.'
bibtex: '@inproceedings{Kersting_Bäumer_2022, place={Barcelona, Spain}, title={Implicit
Statements in Healthcare Reviews: A Challenge for Sentiment Analysis}, booktitle={Proceedings
of the Fourteenth International Conference on Pervasive Patterns and Applications
(PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data
Science for Real-World Applications}, publisher={IARIA}, author={Kersting, Joschka
and Bäumer, Frederik Simon}, editor={Kersting, Joschka}, year={2022}, pages={5–9}
}'
chicago: 'Kersting, Joschka, and Frederik Simon Bäumer. “Implicit Statements in
Healthcare Reviews: A Challenge for Sentiment Analysis.” In Proceedings of
the Fourteenth International Conference on Pervasive Patterns and Applications
(PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data
Science for Real-World Applications, edited by Joschka Kersting, 5–9. Barcelona,
Spain: IARIA, 2022.'
ieee: 'J. Kersting and F. S. Bäumer, “Implicit Statements in Healthcare Reviews:
A Challenge for Sentiment Analysis,” in Proceedings of the Fourteenth International
Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track
AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications,
Barcelona, Spain, 2022, pp. 5–9.'
mla: 'Kersting, Joschka, and Frederik Simon Bäumer. “Implicit Statements in Healthcare
Reviews: A Challenge for Sentiment Analysis.” Proceedings of the Fourteenth
International Conference on Pervasive Patterns and Applications (PATTERNS 2022):
Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World
Applications, edited by Joschka Kersting, IARIA, 2022, pp. 5–9.'
short: 'J. Kersting, F.S. Bäumer, in: J. Kersting (Ed.), Proceedings of the Fourteenth
International Conference on Pervasive Patterns and Applications (PATTERNS 2022):
Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World
Applications, IARIA, Barcelona, Spain, 2022, pp. 5–9.'
conference:
location: Barcelona, Spain
name: The Fourteenth International Conference on Pervasive Patterns and Applications
(PATTERNS 2022)
start_date: 2022-03
date_created: 2022-05-04T08:12:09Z
date_updated: 2022-12-01T13:40:11Z
ddc:
- '006'
editor:
- first_name: Joschka
full_name: Kersting, Joschka
last_name: Kersting
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2022-12-01T13:39:48Z
date_updated: 2022-12-01T13:39:48Z
file_id: '34172'
file_name: Kersting & Bäumer (2022), Kersting2022.pdf
file_size: 155548
relation: main_file
success: 1
file_date_updated: 2022-12-01T13:39:48Z
has_accepted_license: '1'
keyword:
- Sentiment analysis
- Natural language processing
- Aspect phrase extraction
language:
- iso: eng
page: 5-9
place: Barcelona, Spain
project:
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '9'
name: 'SFB 901 - B1: SFB 901 - Subproject B1'
publication: 'Proceedings of the Fourteenth International Conference on Pervasive
Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial
Intelligence - Data Science for Real-World Applications'
publication_status: published
publisher: IARIA
status: public
title: 'Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis'
type: conference
user_id: '58701'
year: '2022'
...
---
_id: '31068'
author:
- first_name: Mei-Hua
full_name: Chen, Mei-Hua
last_name: Chen
- first_name: Garima
full_name: Mudgal, Garima
last_name: Mudgal
- first_name: Wei-Fan
full_name: Chen, Wei-Fan
id: '82920'
last_name: Chen
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: 'Chen M-H, Mudgal G, Chen W-F, Wachsmuth H. Investigating the argumentation
structures of EFL learners from diverse language backgrounds. In: EUROCALL.
; 2022.'
apa: Chen, M.-H., Mudgal, G., Chen, W.-F., & Wachsmuth, H. (2022). Investigating
the argumentation structures of EFL learners from diverse language backgrounds.
EUROCALL.
bibtex: '@inproceedings{Chen_Mudgal_Chen_Wachsmuth_2022, title={Investigating the
argumentation structures of EFL learners from diverse language backgrounds}, booktitle={EUROCALL},
author={Chen, Mei-Hua and Mudgal, Garima and Chen, Wei-Fan and Wachsmuth, Henning},
year={2022} }'
chicago: Chen, Mei-Hua, Garima Mudgal, Wei-Fan Chen, and Henning Wachsmuth. “Investigating
the Argumentation Structures of EFL Learners from Diverse Language Backgrounds.”
In EUROCALL, 2022.
ieee: M.-H. Chen, G. Mudgal, W.-F. Chen, and H. Wachsmuth, “Investigating the argumentation
structures of EFL learners from diverse language backgrounds,” 2022.
mla: Chen, Mei-Hua, et al. “Investigating the Argumentation Structures of EFL Learners
from Diverse Language Backgrounds.” EUROCALL, 2022.
short: 'M.-H. Chen, G. Mudgal, W.-F. Chen, H. Wachsmuth, in: EUROCALL, 2022.'
date_created: 2022-05-05T07:50:21Z
date_updated: 2022-05-09T14:58:39Z
department:
- _id: '600'
language:
- iso: eng
project:
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '9'
name: 'SFB 901 - B1: SFB 901 - Subproject B1'
publication: EUROCALL
status: public
title: Investigating the argumentation structures of EFL learners from diverse language
backgrounds
type: conference_abstract
user_id: '82920'
year: '2022'
...
---
_id: '33033'
author:
- first_name: Lukas
full_name: Fehring, Lukas
id: '75695'
last_name: Fehring
citation:
ama: Fehring L. Combined Ranking and Regression Trees for Algorithm Selection.;
2022.
apa: Fehring, L. (2022). Combined Ranking and Regression Trees for Algorithm
Selection.
bibtex: '@book{Fehring_2022, place={Paderborn}, title={Combined Ranking and Regression
Trees for Algorithm Selection}, author={Fehring, Lukas}, year={2022} }'
chicago: Fehring, Lukas. Combined Ranking and Regression Trees for Algorithm
Selection. Paderborn, 2022.
ieee: L. Fehring, Combined Ranking and Regression Trees for Algorithm Selection.
Paderborn, 2022.
mla: Fehring, Lukas. Combined Ranking and Regression Trees for Algorithm Selection.
2022.
short: L. Fehring, Combined Ranking and Regression Trees for Algorithm Selection,
Paderborn, 2022.
date_created: 2022-08-19T09:41:14Z
date_updated: 2022-08-20T07:02:04Z
ddc:
- '006'
department:
- _id: '34'
- _id: '7'
- _id: '26'
file:
- access_level: open_access
content_type: application/pdf
creator: ahetzer
date_created: 2022-08-19T09:39:57Z
date_updated: 2022-08-19T09:39:57Z
file_id: '33034'
file_name: Final Bachelor Thesis.pdf
file_size: 24830795
relation: main_file
file_date_updated: 2022-08-19T09:39:57Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
place: Paderborn
project:
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '10'
name: 'SFB 901 - B2: SFB 901 - Subproject B2'
status: public
title: Combined Ranking and Regression Trees for Algorithm Selection
type: bachelorsthesis
user_id: '38209'
year: '2022'
...
---
_id: '30867'
abstract:
- lang: eng
text: "In online algorithm selection (OAS), instances of an algorithmic problem\r\nclass
are presented to an agent one after another, and the agent has to quickly\r\nselect
a presumably best algorithm from a fixed set of candidate algorithms.\r\nFor decision
problems such as satisfiability (SAT), quality typically refers to\r\nthe algorithm's
runtime. As the latter is known to exhibit a heavy-tail\r\ndistribution, an algorithm
is normally stopped when exceeding a predefined\r\nupper time limit. As a consequence,
machine learning methods used to optimize\r\nan algorithm selection strategy in
a data-driven manner need to deal with\r\nright-censored samples, a problem that
has received little attention in the\r\nliterature so far. In this work, we revisit
multi-armed bandit algorithms for\r\nOAS and discuss their capability of dealing
with the problem. Moreover, we\r\nadapt them towards runtime-oriented losses,
allowing for partially censored\r\ndata while keeping a space- and time-complexity
independent of the time\r\nhorizon. In an extensive experimental evaluation on
an adapted version of the\r\nASlib benchmark, we demonstrate that theoretically
well-founded methods based\r\non Thompson sampling perform specifically strong
and improve in comparison to\r\nexisting methods."
author:
- first_name: Alexander
full_name: Tornede, Alexander
id: '38209'
last_name: Tornede
- first_name: Viktor
full_name: Bengs, Viktor
id: '76599'
last_name: Bengs
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: Tornede A, Bengs V, Hüllermeier E. Machine Learning for Online Algorithm Selection
under Censored Feedback. Proceedings of the 36th AAAI Conference on Artificial
Intelligence. Published online 2022.
apa: Tornede, A., Bengs, V., & Hüllermeier, E. (2022). Machine Learning for
Online Algorithm Selection under Censored Feedback. In Proceedings of the 36th
AAAI Conference on Artificial Intelligence. AAAI.
bibtex: '@article{Tornede_Bengs_Hüllermeier_2022, title={Machine Learning for Online
Algorithm Selection under Censored Feedback}, journal={Proceedings of the 36th
AAAI Conference on Artificial Intelligence}, publisher={AAAI}, author={Tornede,
Alexander and Bengs, Viktor and Hüllermeier, Eyke}, year={2022} }'
chicago: Tornede, Alexander, Viktor Bengs, and Eyke Hüllermeier. “Machine Learning
for Online Algorithm Selection under Censored Feedback.” Proceedings of the
36th AAAI Conference on Artificial Intelligence. AAAI, 2022.
ieee: A. Tornede, V. Bengs, and E. Hüllermeier, “Machine Learning for Online Algorithm
Selection under Censored Feedback,” Proceedings of the 36th AAAI Conference
on Artificial Intelligence. AAAI, 2022.
mla: Tornede, Alexander, et al. “Machine Learning for Online Algorithm Selection
under Censored Feedback.” Proceedings of the 36th AAAI Conference on Artificial
Intelligence, AAAI, 2022.
short: A. Tornede, V. Bengs, E. Hüllermeier, Proceedings of the 36th AAAI Conference
on Artificial Intelligence (2022).
date_created: 2022-04-12T11:58:56Z
date_updated: 2022-08-24T12:44:27Z
department:
- _id: '34'
- _id: '7'
- _id: '26'
external_id:
arxiv:
- '2109.06234'
language:
- iso: eng
project:
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '10'
name: 'SFB 901 - B2: SFB 901 - Subproject B2'
publication: Proceedings of the 36th AAAI Conference on Artificial Intelligence
publisher: AAAI
status: public
title: Machine Learning for Online Algorithm Selection under Censored Feedback
type: preprint
user_id: '38209'
year: '2022'
...
---
_id: '30865'
abstract:
- lang: eng
text: "The problem of selecting an algorithm that appears most suitable for a\r\nspecific
instance of an algorithmic problem class, such as the Boolean\r\nsatisfiability
problem, is called instance-specific algorithm selection. Over\r\nthe past decade,
the problem has received considerable attention, resulting in\r\na number of different
methods for algorithm selection. Although most of these\r\nmethods are based on
machine learning, surprisingly little work has been done\r\non meta learning,
that is, on taking advantage of the complementarity of\r\nexisting algorithm selection
methods in order to combine them into a single\r\nsuperior algorithm selector.
In this paper, we introduce the problem of meta\r\nalgorithm selection, which
essentially asks for the best way to combine a given\r\nset of algorithm selectors.
We present a general methodological framework for\r\nmeta algorithm selection
as well as several concrete learning methods as\r\ninstantiations of this framework,
essentially combining ideas of meta learning\r\nand ensemble learning. In an extensive
experimental evaluation, we demonstrate\r\nthat ensembles of algorithm selectors
can significantly outperform single\r\nalgorithm selectors and have the potential
to form the new state of the art in\r\nalgorithm selection."
author:
- first_name: Alexander
full_name: Tornede, Alexander
id: '38209'
last_name: Tornede
- first_name: Lukas
full_name: Gehring, Lukas
last_name: Gehring
- first_name: Tanja
full_name: Tornede, Tanja
id: '40795'
last_name: Tornede
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: Tornede A, Gehring L, Tornede T, Wever MD, Hüllermeier E. Algorithm Selection
on a Meta Level. Machine Learning. Published online 2022.
apa: Tornede, A., Gehring, L., Tornede, T., Wever, M. D., & Hüllermeier, E.
(2022). Algorithm Selection on a Meta Level. In Machine Learning.
bibtex: '@article{Tornede_Gehring_Tornede_Wever_Hüllermeier_2022, title={Algorithm
Selection on a Meta Level}, journal={Machine Learning}, author={Tornede, Alexander
and Gehring, Lukas and Tornede, Tanja and Wever, Marcel Dominik and Hüllermeier,
Eyke}, year={2022} }'
chicago: Tornede, Alexander, Lukas Gehring, Tanja Tornede, Marcel Dominik Wever,
and Eyke Hüllermeier. “Algorithm Selection on a Meta Level.” Machine Learning,
2022.
ieee: A. Tornede, L. Gehring, T. Tornede, M. D. Wever, and E. Hüllermeier, “Algorithm
Selection on a Meta Level,” Machine Learning. 2022.
mla: Tornede, Alexander, et al. “Algorithm Selection on a Meta Level.” Machine
Learning, 2022.
short: A. Tornede, L. Gehring, T. Tornede, M.D. Wever, E. Hüllermeier, Machine Learning
(2022).
date_created: 2022-04-12T11:55:18Z
date_updated: 2022-08-24T12:45:39Z
department:
- _id: '34'
- _id: '7'
- _id: '26'
external_id:
arxiv:
- '2107.09414'
language:
- iso: eng
project:
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '10'
name: 'SFB 901 - B2: SFB 901 - Subproject B2'
publication: Machine Learning
status: public
title: Algorithm Selection on a Meta Level
type: preprint
user_id: '38209'
year: '2022'
...
---
_id: '33090'
abstract:
- lang: eng
text: 'AbstractHeated tool butt welding is a method
often used for joining thermoplastics, especially when the components are made
out of different materials. The quality of the connection between the components
crucially depends on a suitable choice of the parameters of the welding process,
such as heating time, temperature, and the precise way how the parts are then
welded. Moreover, when different materials are to be joined, the parameter values
need to be tailored to the specifics of the respective material. To this end,
in this paper, three approaches to tailor the parameter values to optimize the
quality of the connection are compared: a heuristic by Potente, statistical experimental
design, and Bayesian optimization. With the suitability for practice in mind,
a series of experiments are carried out with these approaches, and their capabilities
of proposing well-performing parameter values are investigated. As a result, Bayesian
optimization is found to yield peak performance, but the costs for optimization
are substantial. In contrast, the Potente heuristic does not require any experimentation
and recommends parameter values with competitive quality.'
author:
- first_name: Karina
full_name: Gevers, Karina
id: '83151'
last_name: Gevers
- first_name: Alexander
full_name: Tornede, Alexander
id: '38209'
last_name: Tornede
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Volker
full_name: Schöppner, Volker
id: '20530'
last_name: Schöppner
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: Gevers K, Tornede A, Wever MD, Schöppner V, Hüllermeier E. A comparison of
heuristic, statistical, and machine learning methods for heated tool butt welding
of two different materials. Welding in the World. Published online 2022.
doi:10.1007/s40194-022-01339-9
apa: Gevers, K., Tornede, A., Wever, M. D., Schöppner, V., & Hüllermeier, E.
(2022). A comparison of heuristic, statistical, and machine learning methods for
heated tool butt welding of two different materials. Welding in the World.
https://doi.org/10.1007/s40194-022-01339-9
bibtex: '@article{Gevers_Tornede_Wever_Schöppner_Hüllermeier_2022, title={A comparison
of heuristic, statistical, and machine learning methods for heated tool butt welding
of two different materials}, DOI={10.1007/s40194-022-01339-9},
journal={Welding in the World}, publisher={Springer Science and Business Media
LLC}, author={Gevers, Karina and Tornede, Alexander and Wever, Marcel Dominik
and Schöppner, Volker and Hüllermeier, Eyke}, year={2022} }'
chicago: Gevers, Karina, Alexander Tornede, Marcel Dominik Wever, Volker Schöppner,
and Eyke Hüllermeier. “A Comparison of Heuristic, Statistical, and Machine Learning
Methods for Heated Tool Butt Welding of Two Different Materials.” Welding in
the World, 2022. https://doi.org/10.1007/s40194-022-01339-9.
ieee: 'K. Gevers, A. Tornede, M. D. Wever, V. Schöppner, and E. Hüllermeier, “A
comparison of heuristic, statistical, and machine learning methods for heated
tool butt welding of two different materials,” Welding in the World, 2022,
doi: 10.1007/s40194-022-01339-9.'
mla: Gevers, Karina, et al. “A Comparison of Heuristic, Statistical, and Machine
Learning Methods for Heated Tool Butt Welding of Two Different Materials.” Welding
in the World, Springer Science and Business Media LLC, 2022, doi:10.1007/s40194-022-01339-9.
short: K. Gevers, A. Tornede, M.D. Wever, V. Schöppner, E. Hüllermeier, Welding
in the World (2022).
date_created: 2022-08-24T12:51:07Z
date_updated: 2022-08-24T12:52:06Z
doi: 10.1007/s40194-022-01339-9
keyword:
- Metals and Alloys
- Mechanical Engineering
- Mechanics of Materials
language:
- iso: eng
project:
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '10'
name: 'SFB 901 - B2: SFB 901 - Subproject B2'
publication: Welding in the World
publication_identifier:
issn:
- 0043-2288
- 1878-6669
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: A comparison of heuristic, statistical, and machine learning methods for heated
tool butt welding of two different materials
type: journal_article
user_id: '38209'
year: '2022'
...
---
_id: '53803'
citation:
ama: Kersting J, ed. PATTERNS 2022 The Fourteenth International Conferences on
Pervasive Patterns and Applications. IARIA; 2022.
apa: Kersting, J. (Ed.). (2022). PATTERNS 2022 The Fourteenth International Conferences
on Pervasive Patterns and Applications. IARIA.
bibtex: '@book{Kersting_2022, place={Barcelona, Spain}, title={PATTERNS 2022 The
Fourteenth International Conferences on Pervasive Patterns and Applications},
publisher={IARIA}, year={2022} }'
chicago: 'Kersting, Joschka, ed. PATTERNS 2022 The Fourteenth International Conferences
on Pervasive Patterns and Applications. Barcelona, Spain: IARIA, 2022.'
ieee: 'J. Kersting, Ed., PATTERNS 2022 The Fourteenth International Conferences
on Pervasive Patterns and Applications. Barcelona, Spain: IARIA, 2022.'
mla: Kersting, Joschka, editor. PATTERNS 2022 The Fourteenth International Conferences
on Pervasive Patterns and Applications. IARIA, 2022.
short: J. Kersting, ed., PATTERNS 2022 The Fourteenth International Conferences
on Pervasive Patterns and Applications, IARIA, Barcelona, Spain, 2022.
conference:
end_date: 2022-04-28
location: Barcelona, Spain
name: The Fourteenth International Conferences on Pervasive Patterns and Applications
-- PATTERNS 2022
start_date: 2022-04-24
date_created: 2024-04-30T14:02:14Z
date_updated: 2024-04-30T14:05:40Z
ddc:
- '004'
department:
- _id: '579'
editor:
- first_name: Joschka
full_name: Kersting, Joschka
id: '58701'
last_name: Kersting
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2024-04-30T14:01:07Z
date_updated: 2024-04-30T14:01:07Z
file_id: '53804'
file_name: patterns_2022_full.pdf
file_size: 4578901
relation: main_file
success: 1
file_date_updated: 2024-04-30T14:01:07Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.thinkmind.org/index.php?view=instance&instance=PATTERNS+2022
oa: '1'
place: Barcelona, Spain
project:
- _id: '9'
grant_number: '160364472'
name: 'SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject
B1)'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '1'
grant_number: '160364472'
name: 'SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen
in dynamischen Märkten '
publication_identifier:
unknown:
- 978-1-61208-953-9
publication_status: published
publisher: IARIA
status: public
title: PATTERNS 2022 The Fourteenth International Conferences on Pervasive Patterns
and Applications
type: conference_editor
user_id: '58701'
year: '2022'
...
---
_id: '34041'
author:
- first_name: Linus Matthias
full_name: Witschen, Linus Matthias
id: '49051'
last_name: Witschen
citation:
ama: Witschen LM. Frameworks and Methodologies for Search-Based Approximate Logic
Synthesis.; 2022. doi:10.17619/UNIPB/1-1649
apa: Witschen, L. M. (2022). Frameworks and Methodologies for Search-based Approximate
Logic Synthesis. https://doi.org/10.17619/UNIPB/1-1649
bibtex: '@book{Witschen_2022, title={Frameworks and Methodologies for Search-based
Approximate Logic Synthesis}, DOI={10.17619/UNIPB/1-1649},
author={Witschen, Linus Matthias}, year={2022} }'
chicago: Witschen, Linus Matthias. Frameworks and Methodologies for Search-Based
Approximate Logic Synthesis, 2022. https://doi.org/10.17619/UNIPB/1-1649.
ieee: L. M. Witschen, Frameworks and Methodologies for Search-based Approximate
Logic Synthesis. 2022.
mla: Witschen, Linus Matthias. Frameworks and Methodologies for Search-Based
Approximate Logic Synthesis. 2022, doi:10.17619/UNIPB/1-1649.
short: L.M. Witschen, Frameworks and Methodologies for Search-Based Approximate
Logic Synthesis, 2022.
date_created: 2022-11-09T06:26:22Z
date_updated: 2023-01-19T06:41:22Z
department:
- _id: '78'
doi: 10.17619/UNIPB/1-1649
language:
- iso: eng
project:
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '12'
name: 'SFB 901 - B4: SFB 901 - Subproject B4'
status: public
supervisor:
- first_name: Marco
full_name: Platzner, Marco
id: '398'
last_name: Platzner
title: Frameworks and Methodologies for Search-based Approximate Logic Synthesis
type: dissertation
user_id: '15504'
year: '2022'
...
---
_id: '32342'
author:
- first_name: Qazi Arbab
full_name: Ahmed, Qazi Arbab
id: '72764'
last_name: Ahmed
orcid: 0000-0002-1837-2254
- first_name: Marco
full_name: Platzner, Marco
id: '398'
last_name: Platzner
citation:
ama: 'Ahmed QA, Platzner M. On the Detection and Circumvention of Bitstream-Level
Trojans in FPGAs. In: IEEE Computer Society Annual Symposium on VLSI (ISVLSI,2022);
2022.'
apa: Ahmed, Q. A., & Platzner, M. (2022). On the Detection and Circumvention
of Bitstream-Level Trojans in FPGAs. IEEE Computer Society Annual Symposium
on VLSI Aliathon Resort, Pafos, Cyprus.
bibtex: '@inproceedings{Ahmed_Platzner_2022, place={Pafos, Cyprus}, title={On the
Detection and Circumvention of Bitstream-Level Trojans in FPGAs}, publisher={IEEE
Computer Society Annual Symposium on VLSI (ISVLSI,2022)}, author={Ahmed, Qazi
Arbab and Platzner, Marco}, year={2022} }'
chicago: 'Ahmed, Qazi Arbab, and Marco Platzner. “On the Detection and Circumvention
of Bitstream-Level Trojans in FPGAs.” Pafos, Cyprus: IEEE Computer Society Annual
Symposium on VLSI (ISVLSI,2022), 2022.'
ieee: Q. A. Ahmed and M. Platzner, “On the Detection and Circumvention of Bitstream-Level
Trojans in FPGAs,” presented at the IEEE Computer Society Annual Symposium on
VLSI Aliathon Resort, Pafos, Cyprus, 2022.
mla: Ahmed, Qazi Arbab, and Marco Platzner. On the Detection and Circumvention
of Bitstream-Level Trojans in FPGAs. IEEE Computer Society Annual Symposium
on VLSI (ISVLSI,2022), 2022.
short: 'Q.A. Ahmed, M. Platzner, in: IEEE Computer Society Annual Symposium on VLSI
(ISVLSI,2022), Pafos, Cyprus, 2022.'
conference:
end_date: July 6, 2022
location: Pafos, Cyprus
name: IEEE Computer Society Annual Symposium on VLSI Aliathon Resort,
start_date: ' July 4, 2022'
date_created: 2022-07-12T19:56:48Z
date_updated: 2023-04-19T15:04:30Z
department:
- _id: '78'
language:
- iso: eng
place: Pafos, Cyprus
project:
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '12'
name: 'SFB 901 - B4: SFB 901 - Subproject B4'
publisher: IEEE Computer Society Annual Symposium on VLSI (ISVLSI,2022)
status: public
title: On the Detection and Circumvention of Bitstream-Level Trojans in FPGAs
type: conference
user_id: '72764'
year: '2022'
...
---
_id: '29000'
abstract:
- lang: eng
text: "This thesis aims to provide a bidirectional chatbot solution for the requirement
engineering process. The Sonderforschungsbereich (SFB) 901 intends to provide
the composition of software service On-the-Fly (OTF). The sub-project (B1) of
the SFB 901 project deals with the parameters of service configuration. OTF Computing
aims to eradicate the dependency on the requirement engineers for the software
development process. However, there is no existing bidirectional chatbot solution
that analyses user software requirements and provides viable suggestions to the
user regarding their service. Previously, CORDULA chatbot was developed to analyze
the software requirements but cannot keep the conversation’s context. The Rasa
framework is integrated with the knowledge base to solve the issue, the knowledge
base provides domain-specific knowledge to the chatbot. The software description
is passed through the natural language understanding process to give consciousness
to the chatbot. This process involves various machine learning models, including
app family classification, to correctly identify the domain for user OTF service.
The statistical models like naïve Bayes, kNN and SVM are compared with transformer
models for this classification task. Furthermore, the entities (functional requirements)
are also separated from the user description.\r\nThe chatbot provides the suggestion
of requirements from the preliminary service template with the support of the
knowledge base. Furthermore, the generated response is compared with the state-of-the-art
DialoGPT transformer model and ChatterBot conversational library. These models
are trained over the software development related conversational dataset. All
the responses are ranked using the DialoRPT model, and the BLEU score to evaluates
the models’ responses. Moreover, the chatbot mod- els are tested with human participants,
they used and scored the chatbot responses based on effectiveness, efficiency
and satisfaction. The overall response accuracy is also measured by averaging
the user approval over the generated responses."
author:
- first_name: Mobeen
full_name: Ahmed, Mobeen
last_name: Ahmed
citation:
ama: Ahmed M. Knowledge Base Enhanced & User-Centric Dialogue Design for
OTF Computing.; 2022.
apa: Ahmed, M. (2022). Knowledge Base Enhanced & User-centric Dialogue Design
for OTF Computing.
bibtex: '@book{Ahmed_2022, title={Knowledge Base Enhanced & User-centric Dialogue
Design for OTF Computing}, author={Ahmed, Mobeen}, year={2022} }'
chicago: Ahmed, Mobeen. Knowledge Base Enhanced & User-Centric Dialogue Design
for OTF Computing, 2022.
ieee: M. Ahmed, Knowledge Base Enhanced & User-centric Dialogue Design for
OTF Computing. 2022.
mla: Ahmed, Mobeen. Knowledge Base Enhanced & User-Centric Dialogue Design
for OTF Computing. 2022.
short: M. Ahmed, Knowledge Base Enhanced & User-Centric Dialogue Design for
OTF Computing, 2022.
date_created: 2021-12-16T15:13:07Z
date_updated: 2023-05-02T13:25:45Z
ddc:
- '004'
department:
- _id: '600'
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2023-05-02T13:25:27Z
date_updated: 2023-05-02T13:25:27Z
file_id: '44325'
file_name: Thesis-Report-MOBEEN-AHMED-6856465-Knowledge_Base_Enhanced___User_centric_Dialogue_Design_for_OTFComputing.pdf
file_size: 3092211
relation: main_file
success: 1
file_date_updated: 2023-05-02T13:25:27Z
has_accepted_license: '1'
language:
- iso: eng
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '9'
name: SFB 901 - Subproject B1
publication_status: published
status: public
supervisor:
- first_name: Joschka
full_name: Kersting, Joschka
id: '58701'
last_name: Kersting
title: Knowledge Base Enhanced & User-centric Dialogue Design for OTF Computing
type: mastersthesis
user_id: '58701'
year: '2022'
...
---
_id: '45790'
author:
- first_name: Juela
full_name: Palushi, Juela
last_name: Palushi
citation:
ama: Palushi J. Domain-Aware Text Professionalization Using Sequence-to-Sequence
Neural Networks.; 2022.
apa: Palushi, J. (2022). Domain-aware Text Professionalization using Sequence-to-Sequence
Neural Networks.
bibtex: '@book{Palushi_2022, title={Domain-aware Text Professionalization using
Sequence-to-Sequence Neural Networks}, author={Palushi, Juela}, year={2022} }'
chicago: Palushi, Juela. Domain-Aware Text Professionalization Using Sequence-to-Sequence
Neural Networks, 2022.
ieee: J. Palushi, Domain-aware Text Professionalization using Sequence-to-Sequence
Neural Networks. 2022.
mla: Palushi, Juela. Domain-Aware Text Professionalization Using Sequence-to-Sequence
Neural Networks. 2022.
short: J. Palushi, Domain-Aware Text Professionalization Using Sequence-to-Sequence
Neural Networks, 2022.
date_created: 2023-06-27T12:57:57Z
date_updated: 2023-07-05T07:31:17Z
department:
- _id: '600'
language:
- iso: eng
project:
- _id: '9'
grant_number: '160364472'
name: 'SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject
B1)'
- _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'
status: public
supervisor:
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
title: Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks
type: bachelorsthesis
user_id: '477'
year: '2022'
...
---
_id: '45789'
author:
- first_name: Vinaykumar
full_name: Budanurmath, Vinaykumar
last_name: Budanurmath
citation:
ama: Budanurmath V. Propaganda Technique Detection Using Connotation Frames.;
2022.
apa: Budanurmath, V. (2022). Propaganda Technique Detection Using Connotation
Frames.
bibtex: '@book{Budanurmath_2022, title={Propaganda Technique Detection Using Connotation
Frames}, author={Budanurmath, Vinaykumar}, year={2022} }'
chicago: Budanurmath, Vinaykumar. Propaganda Technique Detection Using Connotation
Frames, 2022.
ieee: V. Budanurmath, Propaganda Technique Detection Using Connotation Frames.
2022.
mla: Budanurmath, Vinaykumar. Propaganda Technique Detection Using Connotation
Frames. 2022.
short: V. Budanurmath, Propaganda Technique Detection Using Connotation Frames,
2022.
date_created: 2023-06-27T12:56:04Z
date_updated: 2023-07-05T07:33:45Z
department:
- _id: '600'
language:
- iso: eng
project:
- _id: '9'
grant_number: '160364472'
name: 'SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject
B1)'
- _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'
status: public
supervisor:
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
title: Propaganda Technique Detection Using Connotation Frames
type: mastersthesis
user_id: '477'
year: '2022'
...
---
_id: '45248'
author:
- first_name: Brijesh
full_name: Dongol, Brijesh
last_name: Dongol
- first_name: Gerhard
full_name: Schellhorn, Gerhard
last_name: Schellhorn
- first_name: Heike
full_name: Wehrheim, Heike
id: '573'
last_name: Wehrheim
citation:
ama: 'Dongol B, Schellhorn G, Wehrheim H. Weak Progressive Forward Simulation Is
Necessary and Sufficient for Strong Observational Refinement. In: Klin B, Lasota
S, Muscholl A, eds. 33rd International Conference on Concurrency Theory, CONCUR
2022, September 12-16, 2022, Warsaw, Poland. Vol 243. LIPIcs. Schloss Dagstuhl
- Leibniz-Zentrum für Informatik; 2022:31:1–31:23. doi:10.4230/LIPIcs.CONCUR.2022.31'
apa: Dongol, B., Schellhorn, G., & Wehrheim, H. (2022). Weak Progressive Forward
Simulation Is Necessary and Sufficient for Strong Observational Refinement. In
B. Klin, S. Lasota, & A. Muscholl (Eds.), 33rd International Conference
on Concurrency Theory, CONCUR 2022, September 12-16, 2022, Warsaw, Poland
(Vol. 243, p. 31:1–31:23). Schloss Dagstuhl - Leibniz-Zentrum für Informatik.
https://doi.org/10.4230/LIPIcs.CONCUR.2022.31
bibtex: '@inproceedings{Dongol_Schellhorn_Wehrheim_2022, series={LIPIcs}, title={Weak
Progressive Forward Simulation Is Necessary and Sufficient for Strong Observational
Refinement}, volume={243}, DOI={10.4230/LIPIcs.CONCUR.2022.31},
booktitle={33rd International Conference on Concurrency Theory, CONCUR 2022, September
12-16, 2022, Warsaw, Poland}, publisher={Schloss Dagstuhl - Leibniz-Zentrum für
Informatik}, author={Dongol, Brijesh and Schellhorn, Gerhard and Wehrheim, Heike},
editor={Klin, Bartek and Lasota, Slawomir and Muscholl, Anca}, year={2022}, pages={31:1–31:23},
collection={LIPIcs} }'
chicago: Dongol, Brijesh, Gerhard Schellhorn, and Heike Wehrheim. “Weak Progressive
Forward Simulation Is Necessary and Sufficient for Strong Observational Refinement.”
In 33rd International Conference on Concurrency Theory, CONCUR 2022, September
12-16, 2022, Warsaw, Poland, edited by Bartek Klin, Slawomir Lasota, and Anca
Muscholl, 243:31:1–31:23. LIPIcs. Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
2022. https://doi.org/10.4230/LIPIcs.CONCUR.2022.31.
ieee: 'B. Dongol, G. Schellhorn, and H. Wehrheim, “Weak Progressive Forward Simulation
Is Necessary and Sufficient for Strong Observational Refinement,” in 33rd International
Conference on Concurrency Theory, CONCUR 2022, September 12-16, 2022, Warsaw,
Poland, 2022, vol. 243, p. 31:1–31:23, doi: 10.4230/LIPIcs.CONCUR.2022.31.'
mla: Dongol, Brijesh, et al. “Weak Progressive Forward Simulation Is Necessary and
Sufficient for Strong Observational Refinement.” 33rd International Conference
on Concurrency Theory, CONCUR 2022, September 12-16, 2022, Warsaw, Poland,
edited by Bartek Klin et al., vol. 243, Schloss Dagstuhl - Leibniz-Zentrum für
Informatik, 2022, p. 31:1–31:23, doi:10.4230/LIPIcs.CONCUR.2022.31.
short: 'B. Dongol, G. Schellhorn, H. Wehrheim, in: B. Klin, S. Lasota, A. Muscholl
(Eds.), 33rd International Conference on Concurrency Theory, CONCUR 2022, September
12-16, 2022, Warsaw, Poland, Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
2022, p. 31:1–31:23.'
date_created: 2023-05-24T07:55:24Z
date_updated: 2023-08-28T12:24:57Z
department:
- _id: '77'
doi: 10.4230/LIPIcs.CONCUR.2022.31
editor:
- first_name: Bartek
full_name: Klin, Bartek
last_name: Klin
- first_name: Slawomir
full_name: Lasota, Slawomir
last_name: Lasota
- first_name: Anca
full_name: Muscholl, Anca
last_name: Muscholl
intvolume: ' 243'
language:
- iso: eng
page: 31:1–31:23
project:
- _id: '1'
grant_number: '160364472'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '12'
name: 'SFB 901 - B4: SFB 901 - Subproject B4'
publication: 33rd International Conference on Concurrency Theory, CONCUR 2022, September
12-16, 2022, Warsaw, Poland
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
series_title: LIPIcs
status: public
title: Weak Progressive Forward Simulation Is Necessary and Sufficient for Strong
Observational Refinement
type: conference
user_id: '477'
volume: 243
year: '2022'
...
---
_id: '30511'
abstract:
- lang: eng
text: AbstractMany critical codebases are written
in C, and most of them use preprocessor directives to encode variability, effectively
encoding software product lines. These preprocessor directives, however, challenge
any static code analysis. SPLlift, a previously presented approach for analyzing
software product lines, is limited to Java programs that use a rather simple feature
encoding and to analysis problems with a finite and ideally small domain. Other
approaches that allow the analysis of real-world C software product lines use
special-purpose analyses, preventing the reuse of existing analysis infrastructures
and ignoring the progress made by the static analysis community. This work presents
VarAlyzer, a novel static analysis approach for software product
lines. VarAlyzer first transforms preprocessor constructs to
plain C while preserving their variability and semantics. It then solves any given
distributive analysis problem on transformed product lines in a variability-aware
manner. VarAlyzer ’s analysis results are annotated with feature
constraints that encode in which configurations each result holds. Our experiments
with 95 compilation units of OpenSSL show that applying VarAlyzer
enables one to conduct inter-procedural, flow-, field- and context-sensitive data-flow
analyses on entire product lines for the first time, outperforming the product-based
approach for highly-configurable systems.
alternative_title:
- Revoking the preprocessor’s special role
article_number: '35'
article_type: original
author:
- first_name: Philipp
full_name: Schubert, Philipp
id: '60543'
last_name: Schubert
orcid: 0000-0002-8674-1859
- first_name: Paul
full_name: Gazzillo, Paul
last_name: Gazzillo
- first_name: Zach
full_name: Patterson, Zach
last_name: Patterson
- first_name: Julian
full_name: Braha, Julian
last_name: Braha
- first_name: Fabian Benedikt
full_name: Schiebel, Fabian Benedikt
id: '55745'
last_name: Schiebel
orcid: 0009-0008-6867-9802
- first_name: Ben
full_name: Hermann, Ben
id: '66173'
last_name: Hermann
orcid: 0000-0001-9848-2017
- first_name: Shiyi
full_name: Wei, Shiyi
last_name: Wei
- first_name: Eric
full_name: Bodden, Eric
id: '59256'
last_name: Bodden
orcid: 0000-0003-3470-3647
citation:
ama: Schubert P, Gazzillo P, Patterson Z, et al. Static data-flow analysis for software
product lines in C. Automated Software Engineering. 2022;29(1). doi:10.1007/s10515-022-00333-1
apa: Schubert, P., Gazzillo, P., Patterson, Z., Braha, J., Schiebel, F. B., Hermann,
B., Wei, S., & Bodden, E. (2022). Static data-flow analysis for software product
lines in C. Automated Software Engineering, 29(1), Article 35. https://doi.org/10.1007/s10515-022-00333-1
bibtex: '@article{Schubert_Gazzillo_Patterson_Braha_Schiebel_Hermann_Wei_Bodden_2022,
title={Static data-flow analysis for software product lines in C}, volume={29},
DOI={10.1007/s10515-022-00333-1},
number={135}, journal={Automated Software Engineering}, publisher={Springer Science
and Business Media LLC}, author={Schubert, Philipp and Gazzillo, Paul and Patterson,
Zach and Braha, Julian and Schiebel, Fabian Benedikt and Hermann, Ben and Wei,
Shiyi and Bodden, Eric}, year={2022} }'
chicago: Schubert, Philipp, Paul Gazzillo, Zach Patterson, Julian Braha, Fabian
Benedikt Schiebel, Ben Hermann, Shiyi Wei, and Eric Bodden. “Static Data-Flow
Analysis for Software Product Lines in C.” Automated Software Engineering
29, no. 1 (2022). https://doi.org/10.1007/s10515-022-00333-1.
ieee: 'P. Schubert et al., “Static data-flow analysis for software product
lines in C,” Automated Software Engineering, vol. 29, no. 1, Art. no. 35,
2022, doi: 10.1007/s10515-022-00333-1.'
mla: Schubert, Philipp, et al. “Static Data-Flow Analysis for Software Product Lines
in C.” Automated Software Engineering, vol. 29, no. 1, 35, Springer Science
and Business Media LLC, 2022, doi:10.1007/s10515-022-00333-1.
short: P. Schubert, P. Gazzillo, Z. Patterson, J. Braha, F.B. Schiebel, B. Hermann,
S. Wei, E. Bodden, Automated Software Engineering 29 (2022).
date_created: 2022-03-25T07:41:26Z
date_updated: 2025-12-04T10:42:38Z
department:
- _id: '76'
doi: 10.1007/s10515-022-00333-1
intvolume: ' 29'
issue: '1'
keyword:
- inter-procedural static analysis
- software product lines
- preprocessor
- LLVM
- C/C++
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://link.springer.com/article/10.1007/s10515-022-00333-1
oa: '1'
project:
- _id: '12'
name: 'SFB 901 - B4: SFB 901 - Subproject B4'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '1'
name: 'SFB 901: SFB 901'
publication: Automated Software Engineering
publication_identifier:
issn:
- 0928-8910
- 1573-7535
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: Static data-flow analysis for software product lines in C
type: journal_article
user_id: '15249'
volume: 29
year: '2022'
...
---
_id: '28350'
abstract:
- lang: eng
text: "In recent years, we observe an increasing amount of software with machine
learning components being deployed. This poses the question of quality assurance
for such components: how can we validate whether specified requirements are fulfilled
by a machine learned software? Current testing and verification approaches either
focus on a single requirement (e.g., fairness) or specialize on a single type
of machine learning model (e.g., neural networks).\r\nIn this paper, we propose
property-driven testing of machine learning models. Our approach MLCheck encompasses
(1) a language for property specification, and (2) a technique for systematic
test case generation. The specification language is comparable to property-based
testing languages. Test case generation employs advanced verification technology
for a systematic, property dependent construction of test suites, without additional
user supplied generator functions. We evaluate MLCheck using requirements and
data sets from three different application areas (software\r\ndiscrimination,
learning on knowledge graphs and security). Our evaluation shows that despite
its generality MLCheck can even outperform specialised testing approaches while
having a comparable runtime"
author:
- first_name: Arnab
full_name: Sharma, Arnab
id: '67200'
last_name: Sharma
- first_name: Caglar
full_name: Demir, Caglar
id: '43817'
last_name: Demir
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
- first_name: Heike
full_name: Wehrheim, Heike
id: '573'
last_name: Wehrheim
citation:
ama: 'Sharma A, Demir C, Ngonga Ngomo A-C, Wehrheim H. MLCHECK–Property-Driven Testing
of Machine Learning Classifiers. In: Proceedings of the 20th IEEE International
Conference on Machine Learning and Applications (ICMLA). IEEE.'
apa: Sharma, A., Demir, C., Ngonga Ngomo, A.-C., & Wehrheim, H. (n.d.). MLCHECK–Property-Driven
Testing of Machine Learning Classifiers. Proceedings of the 20th IEEE International
Conference on Machine Learning and Applications (ICMLA).
bibtex: '@inproceedings{Sharma_Demir_Ngonga Ngomo_Wehrheim, title={MLCHECK–Property-Driven
Testing of Machine Learning Classifiers}, booktitle={Proceedings of the 20th IEEE
International Conference on Machine Learning and Applications (ICMLA)}, publisher={IEEE},
author={Sharma, Arnab and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille and Wehrheim,
Heike} }'
chicago: Sharma, Arnab, Caglar Demir, Axel-Cyrille Ngonga Ngomo, and Heike Wehrheim.
“MLCHECK–Property-Driven Testing of Machine Learning Classifiers.” In Proceedings
of the 20th IEEE International Conference on Machine Learning and Applications
(ICMLA). IEEE, n.d.
ieee: A. Sharma, C. Demir, A.-C. Ngonga Ngomo, and H. Wehrheim, “MLCHECK–Property-Driven
Testing of Machine Learning Classifiers.”
mla: Sharma, Arnab, et al. “MLCHECK–Property-Driven Testing of Machine Learning
Classifiers.” Proceedings of the 20th IEEE International Conference on Machine
Learning and Applications (ICMLA), IEEE.
short: 'A. Sharma, C. Demir, A.-C. Ngonga Ngomo, H. Wehrheim, in: Proceedings of
the 20th IEEE International Conference on Machine Learning and Applications (ICMLA),
IEEE, n.d.'
date_created: 2021-12-07T11:11:36Z
date_updated: 2022-01-06T06:58:02Z
department:
- _id: '7'
- _id: '77'
- _id: '574'
language:
- iso: eng
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '11'
name: SFB 901 - Subproject B3
- _id: '10'
name: SFB 901 - Subproject B2
publication: Proceedings of the 20th IEEE International Conference on Machine Learning
and Applications (ICMLA)
publication_status: accepted
publisher: IEEE
status: public
title: MLCHECK–Property-Driven Testing of Machine Learning Classifiers
type: conference
user_id: '477'
year: '2021'
...
---
_id: '26049'
abstract:
- lang: eng
text: 'Content is the new oil. Users consume billions of terabytes a day while surfing
on news sites or blogs, posting on social media sites, and sending chat messages
around the globe. While content is heterogeneous, the dominant form of web content
is text. There are situations where more diversity needs to be introduced into
text content, for example, to reuse it on websites or to allow a chatbot to base
its models on the information conveyed rather than of the language used. In order
to achieve this, paraphrasing techniques have been developed: One example is Text
spinning, a technique that automatically paraphrases text while leaving the intent
intact. This makes it easier to reuse content, or to change the language generated
by the bot more human. One method for modifying texts is a combination of translation
and back-translation. This paper presents NATTS, a naive approach that uses transformer-based
translation models to create diversified text, combining translation steps in
one model. An advantage of this approach is that it can be fine-tuned and handle
technical language.'
author:
- first_name: Frederik Simon
full_name: Bäumer, Frederik Simon
last_name: Bäumer
- first_name: Joschka
full_name: Kersting, Joschka
id: '58701'
last_name: Kersting
- first_name: Sergej
full_name: Denisov, Sergej
last_name: Denisov
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
citation:
ama: 'Bäumer FS, Kersting J, Denisov S, Geierhos M. IN OTHER WORDS: A NAIVE APPROACH
TO TEXT SPINNING. In: PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET
2021 AND APPLIED COMPUTING 2021. IADIS; 2021:221--225.'
apa: 'Bäumer, F. S., Kersting, J., Denisov, S., & Geierhos, M. (2021). IN OTHER
WORDS: A NAIVE APPROACH TO TEXT SPINNING. PROCEEDINGS OF THE INTERNATIONAL
CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021, 221--225.'
bibtex: '@inproceedings{Bäumer_Kersting_Denisov_Geierhos_2021, title={IN OTHER WORDS:
A NAIVE APPROACH TO TEXT SPINNING}, booktitle={PROCEEDINGS OF THE INTERNATIONAL
CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021}, publisher={IADIS},
author={Bäumer, Frederik Simon and Kersting, Joschka and Denisov, Sergej and Geierhos,
Michaela}, year={2021}, pages={221--225} }'
chicago: 'Bäumer, Frederik Simon, Joschka Kersting, Sergej Denisov, and Michaela
Geierhos. “IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING.” In PROCEEDINGS
OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021,
221--225. IADIS, 2021.'
ieee: 'F. S. Bäumer, J. Kersting, S. Denisov, and M. Geierhos, “IN OTHER WORDS:
A NAIVE APPROACH TO TEXT SPINNING,” in PROCEEDINGS OF THE INTERNATIONAL CONFERENCES
ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021, Lisbon, Portugal, 2021, pp.
221--225.'
mla: 'Bäumer, Frederik Simon, et al. “IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING.”
PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED
COMPUTING 2021, IADIS, 2021, pp. 221--225.'
short: 'F.S. Bäumer, J. Kersting, S. Denisov, M. Geierhos, in: PROCEEDINGS OF THE
INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021, IADIS,
2021, pp. 221--225.'
conference:
end_date: 15.10.2021
location: Lisbon, Portugal
name: 18th International Conference on Applied Computing
start_date: 13.10.2021
date_created: 2021-10-11T15:26:58Z
date_updated: 2022-01-06T06:57:16Z
ddc:
- '000'
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2021-10-15T15:54:41Z
date_updated: 2021-10-15T15:54:41Z
file_id: '26282'
file_name: Bäumer et al. (2021), Baeumer2021.pdf
file_size: 411667
relation: main_file
success: 1
file_date_updated: 2021-10-15T15:54:41Z
has_accepted_license: '1'
keyword:
- Software Requirements
- Natural Language Processing
- Transfer Learning
- On-The-Fly Computing
language:
- iso: eng
page: 221--225
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '9'
name: SFB 901 - Subproject B1
publication: PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND
APPLIED COMPUTING 2021
publisher: IADIS
status: public
title: 'IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING'
type: conference
user_id: '58701'
year: '2021'
...