---
_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: '45863'
abstract:
- lang: eng
text: "In the proposal for our CRC in 2011, we formulated a vision of markets for\r\nIT
services that describes an approach to the provision of such services\r\nthat
was novel at that time and, to a large extent, remains so today:\r\n„Our vision
of on-the-fly computing is that of IT services individually and\r\nautomatically
configured and brought to execution from flexibly combinable\r\nservices traded
on markets. At the same time, we aim at organizing\r\nmarkets whose participants
maintain a lively market of services through\r\nappropriate entrepreneurial actions.“\r\nOver
the last 12 years, we have developed methods and techniques to\r\naddress problems
critical to the convenient, efficient, and secure use of\r\non-the-fly computing.
Among other things, we have made the description\r\nof services more convenient
by allowing natural language input,\r\nincreased the quality of configured services
through (natural language)\r\ninteraction and more efficient configuration processes
and analysis\r\nprocedures, made the quality of (the products of) providers in
the\r\nmarketplace transparent through reputation systems, and increased the\r\nresource
efficiency of execution through reconfigurable heterogeneous\r\ncomputing nodes
and an integrated treatment of service description and\r\nconfiguration. We have
also developed network infrastructures that have\r\na high degree of adaptivity,
scalability, efficiency, and reliability, and\r\nprovide cryptographic guarantees
of anonymity and security for market\r\nparticipants and their products and services.\r\nTo
demonstrate the pervasiveness of the OTF computing approach, we\r\nhave implemented
a proof-of-concept for OTF computing that can run\r\ntypical scenarios of an OTF
market. We illustrated the approach using\r\na cutting-edge application scenario
– automated machine learning (AutoML).\r\nFinally, we have been pushing our work
for the perpetuation of\r\nOn-The-Fly Computing beyond the SFB and sharing the
expertise gained\r\nin the SFB in events with industry partners as well as transfer
projects.\r\nThis work required a broad spectrum of expertise. Computer scientists\r\nand
economists with research interests such as computer networks and\r\ndistributed
algorithms, security and cryptography, software engineering\r\nand verification,
configuration and machine learning, computer engineering\r\nand HPC, microeconomics
and game theory, business informatics\r\nand management have successfully collaborated
here."
alternative_title:
- Collaborative Research Centre 901 (2011 – 2023)
author:
- first_name: Claus-Jochen
full_name: Haake, Claus-Jochen
id: '20801'
last_name: Haake
- first_name: Friedhelm
full_name: Meyer auf der Heide, Friedhelm
id: '15523'
last_name: Meyer auf der Heide
- first_name: Marco
full_name: Platzner, Marco
id: '398'
last_name: Platzner
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
- first_name: Heike
full_name: Wehrheim, Heike
id: '573'
last_name: Wehrheim
citation:
ama: Haake C-J, Meyer auf der Heide F, Platzner M, Wachsmuth H, Wehrheim H. On-The-Fly
Computing -- Individualized IT-Services in Dynamic Markets. Vol 412. Heinz
Nixdorf Institut, Universität Paderborn; 2023. doi:10.17619/UNIPB/1-1797
apa: Haake, C.-J., Meyer auf der Heide, F., Platzner, M., Wachsmuth, H., & Wehrheim,
H. (2023). On-The-Fly Computing -- Individualized IT-services in dynamic markets
(Vol. 412). Heinz Nixdorf Institut, Universität Paderborn. https://doi.org/10.17619/UNIPB/1-1797
bibtex: '@book{Haake_Meyer auf der Heide_Platzner_Wachsmuth_Wehrheim_2023, place={Paderborn},
series={Verlagsschriftenreihe des Heinz Nixdorf Instituts}, title={On-The-Fly
Computing -- Individualized IT-services in dynamic markets}, volume={412}, DOI={10.17619/UNIPB/1-1797}, publisher={Heinz
Nixdorf Institut, Universität Paderborn}, author={Haake, Claus-Jochen and Meyer
auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim,
Heike}, year={2023}, collection={Verlagsschriftenreihe des Heinz Nixdorf Instituts}
}'
chicago: 'Haake, Claus-Jochen, Friedhelm Meyer auf der Heide, Marco Platzner, Henning
Wachsmuth, and Heike Wehrheim. On-The-Fly Computing -- Individualized IT-Services
in Dynamic Markets. Vol. 412. Verlagsschriftenreihe Des Heinz Nixdorf Instituts.
Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023. https://doi.org/10.17619/UNIPB/1-1797.'
ieee: 'C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, and H. Wehrheim,
On-The-Fly Computing -- Individualized IT-services in dynamic markets,
vol. 412. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023.'
mla: Haake, Claus-Jochen, et al. On-The-Fly Computing -- Individualized IT-Services
in Dynamic Markets. Heinz Nixdorf Institut, Universität Paderborn, 2023, doi:10.17619/UNIPB/1-1797.
short: C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim,
On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf
Institut, Universität Paderborn, Paderborn, 2023.
date_created: 2023-07-05T07:16:51Z
date_updated: 2024-07-12T12:07:59Z
ddc:
- '000'
department:
- _id: '7'
- _id: '78'
- _id: '26'
doi: 10.17619/UNIPB/1-1797
file:
- access_level: open_access
content_type: application/pdf
creator: ups
date_created: 2023-07-05T07:15:55Z
date_updated: 2023-07-05T07:19:14Z
file_id: '45864'
file_name: SFB-Buch-Final.pdf
file_size: 15480050
relation: main_file
file_date_updated: 2023-07-05T07:19:14Z
has_accepted_license: '1'
intvolume: ' 412'
language:
- iso: eng
oa: '1'
page: '247'
place: Paderborn
project:
- _id: '1'
grant_number: '160364472'
name: 'SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen
in dynamischen Märkten '
- _id: '2'
name: 'SFB 901 - A: SFB 901 - Project Area A'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '4'
name: 'SFB 901 - C: SFB 901 - Project Area C'
- _id: '82'
name: 'SFB 901 - T: SFB 901 - Project Area T'
- _id: '5'
grant_number: '160364472'
name: 'SFB 901 - A1: SFB 901 - Möglichkeiten und Grenzen lokaler Strategien in dynamischen
Netzen (Subproject A1)'
- _id: '7'
grant_number: '160364472'
name: 'SFB 901 - A3: SFB 901 - Der Markt für Services: Anreize, Algorithmen, Implementation
(Subproject A3)'
- _id: '8'
grant_number: '160364472'
name: 'SFB 901 - A4: SFB 901 - Empirische Analysen in Märkten für OTF Dienstleistungen
(Subproject A4)'
- _id: '9'
grant_number: '160364472'
name: 'SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject
B1)'
- _id: '10'
grant_number: '160364472'
name: 'SFB 901 - B2: Konfiguration und Bewertung (B02)'
- _id: '11'
name: 'SFB 901 - B3: SFB 901 - Subproject B3'
- _id: '12'
name: 'SFB 901 - B4: SFB 901 - Subproject B4'
- _id: '13'
grant_number: '160364472'
name: 'SFB 901 - C1: SFB 901 - Subproject C1'
- _id: '14'
grant_number: '160364472'
name: 'SFB 901 - C2: SFB 901 - On-The-Fly Compute Centers I: Heterogene Ausführungsumgebungen
(Subproject C2)'
- _id: '16'
grant_number: '160364472'
name: 'SFB 901 - C4: SFB 901 - On-The-Fly Compute Centers II: Ausführung komponierter
Dienste in konfigurierbaren Rechenzentren (Subproject C4)'
- _id: '17'
name: 'SFB 901 - C5: SFB 901 - Subproject C5'
- _id: '83'
name: 'SFB 901 - T1: SFB 901 -Subproject T1'
- _id: '84'
grant_number: '160364472'
name: 'SFB 901 - T2: SFB 901 -Subproject T2'
publication_identifier:
unknown:
- 978-3-947647-31-6
publisher: Heinz Nixdorf Institut, Universität Paderborn
series_title: Verlagsschriftenreihe des Heinz Nixdorf Instituts
status: public
title: On-The-Fly Computing -- Individualized IT-services in dynamic markets
type: book
user_id: '1112'
volume: 412
year: '2023'
...
---
_id: '44323'
abstract:
- lang: eng
text: "Reading between the lines has so far been reserved for humans. The present
dissertation addresses this research gap using machine learning methods.\r\nImplicit
expressions are not comprehensible by computers and cannot be localized in the
text. However, many texts arise on interpersonal topics that, unlike commercial
evaluation texts, often imply information only by means of longer phrases. Examples
are the kindness and the attentiveness of a doctor, which are only paraphrased
(“he didn’t even look me in the eye”). The analysis of such data, especially the
identification and localization of implicit statements, is a research gap (1).
This work uses so-called Aspect-based Sentiment Analysis as a method for this
purpose. It remains open how the aspect categories to be extracted can be discovered
and thematically delineated based on the data (2). Furthermore, it is not yet
explored how a collection of tools should look like, with which implicit phrases
can be identified and thus made explicit\r\n(3). Last, it is an open question
how to correlate the identified phrases from the text data with other data, including
the investigation of the relationship between quantitative scores (e.g., school
grades) and the thematically related text (4). Based on these research gaps, the
research question is posed as follows: Using text mining methods, how can implicit
rating content be properly interpreted and thus made explicit before it is automatically
categorized and quantified?\r\nThe uniqueness of this dissertation is based on
the automated recognition of implicit linguistic statements alongside explicit
statements. These are identified in unstructured text data so that features expressed
only in the text can later be compared across data sources, even though they were
not included in rating categories such as stars or school grades. German-language
physician ratings from websites in three countries serve as the sample domain.
The solution approach consists of data creation, a pipeline for text processing
and analyses based on this. In the data creation, aspect classes are identified
and delineated across platforms and marked in text data. This results in six datasets
with over 70,000 annotated sentences and detailed guidelines. The models that
were created based on the training data extract and categorize the aspects. In
addition, the sentiment polarity and the evaluation weight, i. e., the importance
of each phrase, are determined. The models, which are combined in a pipeline,
are used in a prototype in the form of a web application. The analyses built on
the pipeline quantify the rating contents by linking the obtained information
with further data, thus allowing new insights.\r\nAs a result, a toolbox is provided
to identify quantifiable rating content and categories using text mining for a
sample domain. This is used to evaluate the approach, which in principle can also
be adapted to any other domain."
author:
- first_name: Joschka
full_name: Kersting, Joschka
id: '58701'
last_name: Kersting
citation:
ama: Kersting J. Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien
mittels Text Mining. Universität der Bundeswehr München ; 2023.
apa: Kersting, J. (2023). Identifizierung quantifizierbarer Bewertungsinhalte
und -kategorien mittels Text Mining. Universität der Bundeswehr München .
bibtex: '@book{Kersting_2023, place={Neubiberg}, title={Identifizierung quantifizierbarer
Bewertungsinhalte und -kategorien mittels Text Mining}, publisher={Universität
der Bundeswehr München }, author={Kersting, Joschka}, year={2023} }'
chicago: 'Kersting, Joschka. Identifizierung quantifizierbarer Bewertungsinhalte
und -kategorien mittels Text Mining. Neubiberg: Universität der Bundeswehr
München , 2023.'
ieee: 'J. Kersting, Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien
mittels Text Mining. Neubiberg: Universität der Bundeswehr München , 2023.'
mla: Kersting, Joschka. Identifizierung quantifizierbarer Bewertungsinhalte und
-kategorien mittels Text Mining. Universität der Bundeswehr München , 2023.
short: J. Kersting, Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien
mittels Text Mining, Universität der Bundeswehr München , Neubiberg, 2023.
date_created: 2023-05-02T12:54:00Z
date_updated: 2023-07-03T12:29:50Z
department:
- _id: '579'
- _id: '7'
language:
- iso: ger
page: '208'
place: Neubiberg
project:
- _id: '1'
grant_number: '160364472'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '9'
grant_number: '160364472'
name: 'SFB 901 - B1: SFB 901 - Subproject B1'
publication_status: published
publisher: 'Universität der Bundeswehr München '
related_material:
link:
- relation: supplementary_material
url: https://athene-forschung.unibw.de/145003
status: public
supervisor:
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
title: Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels
Text Mining
type: dissertation
user_id: '58701'
year: '2023'
...
---
_id: '45882'
author:
- first_name: Frederik Simon
full_name: Bäumer, Frederik Simon
id: '38837'
last_name: Bäumer
- first_name: Wei-Fan
full_name: Chen, Wei-Fan
id: '82920'
last_name: Chen
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
- first_name: Joschka
full_name: Kersting, Joschka
id: '58701'
last_name: Kersting
- first_name: Henning
full_name: Wachsmuth, Henning
last_name: Wachsmuth
citation:
ama: 'Bäumer FS, Chen W-F, Geierhos M, Kersting J, Wachsmuth H. Dialogue-based Requirement
Compensation and Style-adjusted Data-to-text Generation. In: Haake C-J, Meyer
auf der Heide F, Platzner M, Wachsmuth H, Wehrheim H, eds. On-The-Fly Computing
-- Individualized IT-Services in Dynamic Markets. Vol 412. Verlagsschriftenreihe
des Heinz Nixdorf Instituts. Heinz Nixdorf Institut, Universität Paderborn; 2023:65-84.
doi:10.5281/zenodo.8068456'
apa: Bäumer, F. S., Chen, W.-F., Geierhos, M., Kersting, J., & Wachsmuth, H.
(2023). Dialogue-based Requirement Compensation and Style-adjusted Data-to-text
Generation. In C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth,
& H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-services
in dynamic markets (Vol. 412, pp. 65–84). Heinz Nixdorf Institut, Universität
Paderborn. https://doi.org/10.5281/zenodo.8068456
bibtex: '@inbook{Bäumer_Chen_Geierhos_Kersting_Wachsmuth_2023, place={Paderborn},
series={Verlagsschriftenreihe des Heinz Nixdorf Instituts}, title={Dialogue-based
Requirement Compensation and Style-adjusted Data-to-text Generation}, volume={412},
DOI={10.5281/zenodo.8068456},
booktitle={On-The-Fly Computing -- Individualized IT-services in dynamic markets},
publisher={Heinz Nixdorf Institut, Universität Paderborn}, author={Bäumer, Frederik
Simon and Chen, Wei-Fan and Geierhos, Michaela and Kersting, Joschka and Wachsmuth,
Henning}, editor={Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner,
Marco and Wachsmuth, Henning and Wehrheim, Heike}, year={2023}, pages={65–84},
collection={Verlagsschriftenreihe des Heinz Nixdorf Instituts} }'
chicago: 'Bäumer, Frederik Simon, Wei-Fan Chen, Michaela Geierhos, Joschka Kersting,
and Henning Wachsmuth. “Dialogue-Based Requirement Compensation and Style-Adjusted
Data-to-Text Generation.” In On-The-Fly Computing -- Individualized IT-Services
in Dynamic Markets, edited by Claus-Jochen Haake, Friedhelm Meyer auf der
Heide, Marco Platzner, Henning Wachsmuth, and Heike Wehrheim, 412:65–84. Verlagsschriftenreihe
Des Heinz Nixdorf Instituts. Paderborn: Heinz Nixdorf Institut, Universität Paderborn,
2023. https://doi.org/10.5281/zenodo.8068456.'
ieee: 'F. S. Bäumer, W.-F. Chen, M. Geierhos, J. Kersting, and H. Wachsmuth, “Dialogue-based
Requirement Compensation and Style-adjusted Data-to-text Generation,” in On-The-Fly
Computing -- Individualized IT-services in dynamic markets, vol. 412, C.-J.
Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, and H. Wehrheim, Eds.
Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 65–84.'
mla: Bäumer, Frederik Simon, et al. “Dialogue-Based Requirement Compensation and
Style-Adjusted Data-to-Text Generation.” On-The-Fly Computing -- Individualized
IT-Services in Dynamic Markets, edited by Claus-Jochen Haake et al., vol.
412, Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 65–84, doi:10.5281/zenodo.8068456.
short: 'F.S. Bäumer, W.-F. Chen, M. Geierhos, J. Kersting, H. Wachsmuth, in: C.-J.
Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim (Eds.),
On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf
Institut, Universität Paderborn, Paderborn, 2023, pp. 65–84.'
date_created: 2023-07-07T07:29:13Z
date_updated: 2023-07-07T11:20:52Z
ddc:
- '004'
department:
- _id: '7'
- _id: '369'
doi: 10.5281/zenodo.8068456
editor:
- first_name: Claus-Jochen
full_name: Haake, Claus-Jochen
last_name: Haake
- first_name: Friedhelm
full_name: Meyer auf der Heide, Friedhelm
last_name: Meyer auf der Heide
- first_name: Marco
full_name: Platzner, Marco
last_name: Platzner
- first_name: Henning
full_name: Wachsmuth, Henning
last_name: Wachsmuth
- first_name: Heike
full_name: Wehrheim, Heike
last_name: Wehrheim
file:
- access_level: open_access
content_type: application/pdf
creator: florida
date_created: 2023-07-07T07:28:58Z
date_updated: 2023-07-07T11:20:52Z
file_id: '45883'
file_name: B1-Chapter-SFB-Buch-Final.pdf
file_size: 1342718
relation: main_file
file_date_updated: 2023-07-07T11:20:52Z
has_accepted_license: '1'
intvolume: ' 412'
language:
- iso: eng
oa: '1'
page: 65-84
place: Paderborn
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: On-The-Fly Computing -- Individualized IT-services in dynamic markets
publisher: Heinz Nixdorf Institut, Universität Paderborn
series_title: Verlagsschriftenreihe des Heinz Nixdorf Instituts
status: public
title: Dialogue-based Requirement Compensation and Style-adjusted Data-to-text Generation
type: book_chapter
user_id: '477'
volume: 412
year: '2023'
...
---
_id: '46205'
abstract:
- lang: eng
text: We present a concept for quantifying evaluative phrases to later compare rating
texts numerically instead of just relying on stars or grades. We achievethis by
combining deep learning models in an aspect-based sentiment analysis pipeline
along with sentiment weighting, polarity, and correlation analyses that combine
deep learning results with metadata. The results provide new insights for the
medical field. Our application domain, physician reviews, shows that there are
millions of review texts on the Internet that cannot yet be comprehensively analyzed
because previous studies have focused on explicit aspects from other domains (e.g.,
products). We identify, extract, and classify implicit and explicit aspect phrases
equally from German-language review texts. To do so, we annotated aspect phrases
representing reviews on numerous aspects of a physician, medical practice, or
practice staff. We apply the best performing transformer model, XLM-RoBERTa, to
a large physician review dataset and correlate the results with existing metadata.
As a result, we can show different correlations between the sentiment polarity
of certain aspect classes (e.g., friendliness, practice equipment) and physicians’
professions (e.g., surgeon, ophthalmologist). As a result, we have individual
numerical scores that contain a variety of information based on deep learning
algorithms that extract textual (evaluative) information and metadata from the
Web.
author:
- first_name: Joschka
full_name: Kersting, Joschka
id: '58701'
last_name: Kersting
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
citation:
ama: 'Kersting J, Geierhos M. Towards Comparable Ratings: Quantifying Evaluative
Phrases in Physician Reviews. In: Cuzzocrea A, Gusikhin O, Hammoudi S, Quix C,
eds. Data Management Technologies and Applications. Vol 1860. Communications
in Computer and Information Science. Springer Nature Switzerland; 2023:45-65.
doi:10.1007/978-3-031-37890-4_3'
apa: 'Kersting, J., & Geierhos, M. (2023). Towards Comparable Ratings: Quantifying
Evaluative Phrases in Physician Reviews. In A. Cuzzocrea, O. Gusikhin, S. Hammoudi,
& C. Quix (Eds.), Data Management Technologies and Applications (Vol.
1860, pp. 45–65). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-37890-4_3'
bibtex: '@inbook{Kersting_Geierhos_2023, place={Cham}, series={Communications in
Computer and Information Science}, title={Towards Comparable Ratings: Quantifying
Evaluative Phrases in Physician Reviews}, volume={1860}, DOI={10.1007/978-3-031-37890-4_3},
booktitle={Data Management Technologies and Applications}, publisher={Springer
Nature Switzerland}, author={Kersting, Joschka and Geierhos, Michaela}, editor={Cuzzocrea,
Alfredo and Gusikhin, Oleg and Hammoudi, Slimane and Quix, Christoph}, year={2023},
pages={45–65}, collection={Communications in Computer and Information Science}
}'
chicago: 'Kersting, Joschka, and Michaela Geierhos. “Towards Comparable Ratings:
Quantifying Evaluative Phrases in Physician Reviews.” In Data Management Technologies
and Applications, edited by Alfredo Cuzzocrea, Oleg Gusikhin, Slimane Hammoudi,
and Christoph Quix, 1860:45–65. Communications in Computer and Information Science.
Cham: Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-37890-4_3.'
ieee: 'J. Kersting and M. Geierhos, “Towards Comparable Ratings: Quantifying Evaluative
Phrases in Physician Reviews,” in Data Management Technologies and Applications,
vol. 1860, A. Cuzzocrea, O. Gusikhin, S. Hammoudi, and C. Quix, Eds. Cham: Springer
Nature Switzerland, 2023, pp. 45–65.'
mla: 'Kersting, Joschka, and Michaela Geierhos. “Towards Comparable Ratings: Quantifying
Evaluative Phrases in Physician Reviews.” Data Management Technologies and
Applications, edited by Alfredo Cuzzocrea et al., vol. 1860, Springer Nature
Switzerland, 2023, pp. 45–65, doi:10.1007/978-3-031-37890-4_3.'
short: 'J. Kersting, M. Geierhos, in: A. Cuzzocrea, O. Gusikhin, S. Hammoudi, C.
Quix (Eds.), Data Management Technologies and Applications, Springer Nature Switzerland,
Cham, 2023, pp. 45–65.'
date_created: 2023-07-28T15:03:14Z
date_updated: 2023-07-28T15:11:10Z
ddc:
- '004'
department:
- _id: '579'
doi: 10.1007/978-3-031-37890-4_3
editor:
- first_name: Alfredo
full_name: Cuzzocrea, Alfredo
last_name: Cuzzocrea
- first_name: Oleg
full_name: Gusikhin, Oleg
last_name: Gusikhin
- first_name: Slimane
full_name: Hammoudi, Slimane
last_name: Hammoudi
- first_name: Christoph
full_name: Quix, Christoph
last_name: Quix
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2023-07-28T15:10:48Z
date_updated: 2023-07-28T15:10:48Z
file_id: '46207'
file_name: Kersting and Geierhos (2023), Kersting2023b.pdf
file_size: 746336
relation: main_file
success: 1
file_date_updated: 2023-07-28T15:10:48Z
has_accepted_license: '1'
intvolume: ' 1860'
language:
- iso: eng
page: 45-65
place: Cham
project:
- _id: '1'
grant_number: '160364472'
name: 'SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen
in dynamischen Märkten '
- _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'
publication: Data Management Technologies and Applications
publication_identifier:
isbn:
- '9783031378898'
- '9783031378904'
issn:
- 1865-0929
- 1865-0937
publication_status: published
publisher: Springer Nature Switzerland
series_title: Communications in Computer and Information Science
status: public
title: 'Towards Comparable Ratings: Quantifying Evaluative Phrases in Physician Reviews'
type: book_chapter
user_id: '58701'
volume: 1860
year: '2023'
...
---
_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: '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: '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: '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'
...
---
_id: '17905'
abstract:
- lang: eng
text: 'This chapter concentrates on aspect-based sentiment analysis, a form of opinion
mining where algorithms detect sentiments expressed about features of products,
services, etc. We especially focus on novel approaches for aspect phrase extraction
and classification trained on feature-rich datasets. Here, we present two new
datasets, which we gathered from the linguistically rich domain of physician reviews,
as other investigations have mainly concentrated on commercial reviews and social
media reviews so far. To give readers a better understanding of the underlying
datasets, we describe the annotation process and inter-annotator agreement in
detail. In our research, we automatically assess implicit mentions or indications
of specific aspects. To do this, we propose and utilize neural network models
that perform the here-defined aspect phrase extraction and classification task,
achieving F1-score values of about 80% and accuracy values of more than 90%. As
we apply our models to a comparatively complex domain, we obtain promising results. '
author:
- first_name: Joschka
full_name: Kersting, Joschka
id: '58701'
last_name: Kersting
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
citation:
ama: 'Kersting J, Geierhos M. Towards Aspect Extraction and Classification for Opinion
Mining with Deep Sequence Networks. In: Loukanova R, ed. Natural Language Processing
in Artificial Intelligence -- NLPinAI 2020. Vol 939. Studies in Computational
Intelligence (SCI). Cham: Springer; 2021:163--189. doi:10.1007/978-3-030-63787-3_6'
apa: 'Kersting, J., & Geierhos, M. (2021). Towards Aspect Extraction and Classification
for Opinion Mining with Deep Sequence Networks. In R. Loukanova (Ed.), Natural
Language Processing in Artificial Intelligence -- NLPinAI 2020 (Vol. 939,
pp. 163--189). Cham: Springer. https://doi.org/10.1007/978-3-030-63787-3_6'
bibtex: '@inbook{Kersting_Geierhos_2021, place={Cham}, series={Studies in Computational
Intelligence (SCI)}, title={Towards Aspect Extraction and Classification for Opinion
Mining with Deep Sequence Networks}, volume={939}, DOI={10.1007/978-3-030-63787-3_6},
booktitle={Natural Language Processing in Artificial Intelligence -- NLPinAI 2020},
publisher={Springer}, author={Kersting, Joschka and Geierhos, Michaela}, editor={Loukanova,
RoussankaEditor}, year={2021}, pages={163--189}, collection={Studies in Computational
Intelligence (SCI)} }'
chicago: 'Kersting, Joschka, and Michaela Geierhos. “Towards Aspect Extraction and
Classification for Opinion Mining with Deep Sequence Networks.” In Natural
Language Processing in Artificial Intelligence -- NLPinAI 2020, edited by
Roussanka Loukanova, 939:163--189. Studies in Computational Intelligence (SCI).
Cham: Springer, 2021. https://doi.org/10.1007/978-3-030-63787-3_6.'
ieee: 'J. Kersting and M. Geierhos, “Towards Aspect Extraction and Classification
for Opinion Mining with Deep Sequence Networks,” in Natural Language Processing
in Artificial Intelligence -- NLPinAI 2020, vol. 939, R. Loukanova, Ed. Cham:
Springer, 2021, pp. 163--189.'
mla: Kersting, Joschka, and Michaela Geierhos. “Towards Aspect Extraction and Classification
for Opinion Mining with Deep Sequence Networks.” Natural Language Processing
in Artificial Intelligence -- NLPinAI 2020, edited by Roussanka Loukanova,
vol. 939, Springer, 2021, pp. 163--189, doi:10.1007/978-3-030-63787-3_6.
short: 'J. Kersting, M. Geierhos, in: R. Loukanova (Ed.), Natural Language Processing
in Artificial Intelligence -- NLPinAI 2020, Springer, Cham, 2021, pp. 163--189.'
date_created: 2020-08-13T09:29:52Z
date_updated: 2022-01-06T06:53:23Z
ddc:
- '000'
department:
- _id: '579'
doi: 10.1007/978-3-030-63787-3_6
editor:
- first_name: Roussanka
full_name: Loukanova, Roussanka
last_name: Loukanova
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2021-04-08T08:14:05Z
date_updated: 2021-04-08T08:14:05Z
file_id: '21594'
file_name: Kersting-Geierhos2021_Chapter_TowardsAspectExtractionAndClas.pdf
file_size: 512065
relation: main_file
success: 1
file_date_updated: 2021-04-08T08:14:05Z
has_accepted_license: '1'
intvolume: ' 939'
language:
- iso: eng
page: '163--189 '
place: Cham
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '9'
name: SFB 901 - Subproject B1
publication: Natural Language Processing in Artificial Intelligence -- NLPinAI 2020
publication_identifier:
unknown:
- 978-3-030-63786-6 ; 978-3-030-63787-3
publication_status: published
publisher: Springer
series_title: Studies in Computational Intelligence (SCI)
status: public
title: Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence
Networks
type: book_chapter
user_id: '58701'
volume: 939
year: '2021'
...
---
_id: '22051'
author:
- first_name: Joschka
full_name: Kersting, Joschka
id: '58701'
last_name: Kersting
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
citation:
ama: 'Kersting J, Geierhos M. Well-being in Plastic Surgery: Deep Learning Reveals
Patients’ Evaluations. In: Proceedings of the 10th International Conference
on Data Science, Technology and Applications (DATA 2021). SCITEPRESS; 2021:275--284.'
apa: 'Kersting, J., & Geierhos, M. (2021). Well-being in Plastic Surgery: Deep
Learning Reveals Patients’ Evaluations. Proceedings of the 10th International
Conference on Data Science, Technology and Applications (DATA 2021), 275--284.'
bibtex: '@inproceedings{Kersting_Geierhos_2021, place={Online}, title={Well-being
in Plastic Surgery: Deep Learning Reveals Patients’ Evaluations}, booktitle={Proceedings
of the 10th International Conference on Data Science, Technology and Applications
(DATA 2021)}, publisher={SCITEPRESS}, author={Kersting, Joschka and Geierhos,
Michaela}, year={2021}, pages={275--284} }'
chicago: 'Kersting, Joschka, and Michaela Geierhos. “Well-Being in Plastic Surgery:
Deep Learning Reveals Patients’ Evaluations.” In Proceedings of the 10th International
Conference on Data Science, Technology and Applications (DATA 2021), 275--284.
Online: SCITEPRESS, 2021.'
ieee: 'J. Kersting and M. Geierhos, “Well-being in Plastic Surgery: Deep Learning
Reveals Patients’ Evaluations,” in Proceedings of the 10th International Conference
on Data Science, Technology and Applications (DATA 2021), Online, 2021, pp.
275--284.'
mla: 'Kersting, Joschka, and Michaela Geierhos. “Well-Being in Plastic Surgery:
Deep Learning Reveals Patients’ Evaluations.” Proceedings of the 10th International
Conference on Data Science, Technology and Applications (DATA 2021), SCITEPRESS,
2021, pp. 275--284.'
short: 'J. Kersting, M. Geierhos, in: Proceedings of the 10th International Conference
on Data Science, Technology and Applications (DATA 2021), SCITEPRESS, Online,
2021, pp. 275--284.'
conference:
end_date: 2021-07-08
location: Online
name: 10th International Conference on Data Science, Technology and Applications
(DATA 2021)
start_date: 2021-07-06
date_created: 2021-05-07T16:27:27Z
date_updated: 2022-01-06T06:55:23Z
department:
- _id: '579'
language:
- iso: eng
page: 275--284
place: Online
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 10th International Conference on Data Science, Technology
and Applications (DATA 2021)
publication_status: published
publisher: SCITEPRESS
status: public
title: 'Well-being in Plastic Surgery: Deep Learning Reveals Patients'' Evaluations'
type: conference
user_id: '58701'
year: '2021'
...
---
_id: '22052'
abstract:
- lang: eng
text: In this study, we describe a text processing pipeline that transforms user-generated
text into structured data. To do this, we train neural and transformer-based models
for aspect-based sentiment analysis. As most research deals with explicit aspects
from product or service data, we extract and classify implicit and explicit aspect
phrases from German-language physician review texts. Patients often rate on the
basis of perceived friendliness or competence. The vocabulary is difficult, the
topic sensitive, and the data user-generated. The aspect phrases come with various
wordings using insertions and are not noun-based, which makes the presented case
equally relevant and reality-based. To find complex, indirect aspect phrases,
up-to-date deep learning approaches must be combined with supervised training
data. We describe three aspect phrase datasets, one of them new, as well as a
newly annotated aspect polarity dataset. Alongside this, we build an algorithm
to rate the aspect phrase importance. All in all, we train eight transformers
on the new raw data domain, compare 54 neural aspect extraction models and, based
on this, create eight aspect polarity models for our pipeline. These models are
evaluated by using Precision, Recall, and F-Score measures. Finally, we evaluate
our aspect phrase importance measure algorithm.
author:
- first_name: Joschka
full_name: Kersting, Joschka
id: '58701'
last_name: Kersting
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
citation:
ama: 'Kersting J, Geierhos M. Human Language Comprehension in Aspect Phrase Extraction
with Importance Weighting. In: Kapetanios E, Horacek H, Métais E, Meziane F, eds.
Natural Language Processing and Information Systems. Vol 12801. Lecture
Notes in Computer Science. Springer; 2021:231--242.'
apa: Kersting, J., & Geierhos, M. (2021). Human Language Comprehension in Aspect
Phrase Extraction with Importance Weighting. In E. Kapetanios, H. Horacek, E.
Métais, & F. Meziane (Eds.), Natural Language Processing and Information
Systems (Vol. 12801, pp. 231--242). Springer.
bibtex: '@inbook{Kersting_Geierhos_2021, place={Saarbrücken, Germany}, series={Lecture
Notes in Computer Science}, title={Human Language Comprehension in Aspect Phrase
Extraction with Importance Weighting}, volume={12801}, booktitle={Natural Language
Processing and Information Systems}, publisher={Springer}, author={Kersting, Joschka
and Geierhos, Michaela}, editor={Kapetanios, Epaminondas and Horacek, Helmut and
Métais, Elisabeth and Meziane, Farid}, year={2021}, pages={231--242}, collection={Lecture
Notes in Computer Science} }'
chicago: 'Kersting, Joschka, and Michaela Geierhos. “Human Language Comprehension
in Aspect Phrase Extraction with Importance Weighting.” In Natural Language
Processing and Information Systems, edited by Epaminondas Kapetanios, Helmut
Horacek, Elisabeth Métais, and Farid Meziane, 12801:231--242. Lecture Notes in
Computer Science. Saarbrücken, Germany: Springer, 2021.'
ieee: 'J. Kersting and M. Geierhos, “Human Language Comprehension in Aspect Phrase
Extraction with Importance Weighting,” in Natural Language Processing and Information
Systems, vol. 12801, E. Kapetanios, H. Horacek, E. Métais, and F. Meziane,
Eds. Saarbrücken, Germany: Springer, 2021, pp. 231--242.'
mla: Kersting, Joschka, and Michaela Geierhos. “Human Language Comprehension in
Aspect Phrase Extraction with Importance Weighting.” Natural Language Processing
and Information Systems, edited by Epaminondas Kapetanios et al., vol. 12801,
Springer, 2021, pp. 231--242.
short: 'J. Kersting, M. Geierhos, in: E. Kapetanios, H. Horacek, E. Métais, F. Meziane
(Eds.), Natural Language Processing and Information Systems, Springer, Saarbrücken,
Germany, 2021, pp. 231--242.'
conference:
end_date: 2021-06-25
location: Saarbrücken, Germany
name: 26th International Conference on Natural Language & Information Systems (NLDB
2021)
start_date: 2021-06-23
date_created: 2021-05-07T16:31:05Z
date_updated: 2022-07-14T08:00:56Z
ddc:
- '004'
department:
- _id: '579'
editor:
- first_name: Epaminondas
full_name: Kapetanios, Epaminondas
last_name: Kapetanios
- first_name: Helmut
full_name: Horacek, Helmut
last_name: Horacek
- first_name: Elisabeth
full_name: Métais, Elisabeth
last_name: Métais
- first_name: Farid
full_name: Meziane, Farid
last_name: Meziane
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2022-07-14T08:00:35Z
date_updated: 2022-07-14T08:00:35Z
file_id: '32362'
file_name: Kersting & Geierhos (2021b), Kersting2021b.pdf
file_size: 506329
relation: main_file
success: 1
file_date_updated: 2022-07-14T08:00:35Z
has_accepted_license: '1'
intvolume: ' 12801'
language:
- iso: eng
page: 231--242
place: Saarbrücken, Germany
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '9'
name: SFB 901 - Subproject B1
publication: Natural Language Processing and Information Systems
publication_status: published
publisher: Springer
series_title: Lecture Notes in Computer Science
status: public
title: Human Language Comprehension in Aspect Phrase Extraction with Importance Weighting
type: book_chapter
user_id: '58701'
volume: 12801
year: '2021'
...
---
_id: '23709'
author:
- first_name: Wei-Fan
full_name: Chen, Wei-Fan
id: '82920'
last_name: Chen
- first_name: Khalid
full_name: Al Khatib, Khalid
last_name: Al Khatib
- first_name: Benno
full_name: Stein, Benno
last_name: Stein
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: 'Chen W-F, Al Khatib K, Stein B, Wachsmuth H. Controlled Neural Sentence-Level
Reframing of News Articles. In: Findings of the Association for Computational
Linguistics: EMNLP 2021. ; 2021:2683-2693.'
apa: 'Chen, W.-F., Al Khatib, K., Stein, B., & Wachsmuth, H. (2021). Controlled
Neural Sentence-Level Reframing of News Articles. Findings of the Association
for Computational Linguistics: EMNLP 2021, 2683–2693.'
bibtex: '@inproceedings{Chen_Al Khatib_Stein_Wachsmuth_2021, title={Controlled Neural
Sentence-Level Reframing of News Articles}, booktitle={Findings of the Association
for Computational Linguistics: EMNLP 2021}, author={Chen, Wei-Fan and Al Khatib,
Khalid and Stein, Benno and Wachsmuth, Henning}, year={2021}, pages={2683–2693}
}'
chicago: 'Chen, Wei-Fan, Khalid Al Khatib, Benno Stein, and Henning Wachsmuth. “Controlled
Neural Sentence-Level Reframing of News Articles.” In Findings of the Association
for Computational Linguistics: EMNLP 2021, 2683–93, 2021.'
ieee: 'W.-F. Chen, K. Al Khatib, B. Stein, and H. Wachsmuth, “Controlled Neural
Sentence-Level Reframing of News Articles,” in Findings of the Association
for Computational Linguistics: EMNLP 2021, 2021, pp. 2683–2693.'
mla: 'Chen, Wei-Fan, et al. “Controlled Neural Sentence-Level Reframing of News
Articles.” Findings of the Association for Computational Linguistics: EMNLP
2021, 2021, pp. 2683–93.'
short: 'W.-F. Chen, K. Al Khatib, B. Stein, H. Wachsmuth, in: Findings of the Association
for Computational Linguistics: EMNLP 2021, 2021, pp. 2683–2693.'
date_created: 2021-09-02T20:09:20Z
date_updated: 2022-05-09T15:00:09Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- url: https://aclanthology.org/2021.findings-emnlp.228.pdf
page: 2683 - 2693
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: 'Findings of the Association for Computational Linguistics: EMNLP 2021'
status: public
title: Controlled Neural Sentence-Level Reframing of News Articles
type: conference
user_id: '82920'
year: '2021'
...
---
_id: '22229'
author:
- first_name: Milad
full_name: Alshomary, Milad
id: '73059'
last_name: Alshomary
- first_name: Shahbaz
full_name: Syed, Shahbaz
last_name: Syed
- first_name: Martin
full_name: Potthast, Martin
last_name: Potthast
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: 'Alshomary M, Syed S, Potthast M, Wachsmuth H. Argument Undermining: Counter-Argument
Generation by Attacking Weak Premises. In: Proceedings of the Joint Conference
of the 59th Annual Meeting of the Association for Computational Linguistics and
the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP
2021). Findings of the Association for Computational Linguistics: ACL-IJCNLP
2021. Association for Computational Linguistics; 2021:1816–1827. doi:10.18653/v1/2021.findings-acl.159'
apa: 'Alshomary, M., Syed, S., Potthast, M., & Wachsmuth, H. (2021). Argument
Undermining: Counter-Argument Generation by Attacking Weak Premises. Proceedings
of the Joint Conference of the 59th Annual Meeting of the Association for Computational
Linguistics and the 11th International Joint Conference on Natural Language Processing
(ACL-IJCNLP 2021), 1816–1827. https://doi.org/10.18653/v1/2021.findings-acl.159'
bibtex: '@inproceedings{Alshomary_Syed_Potthast_Wachsmuth_2021, series={Findings
of the Association for Computational Linguistics: ACL-IJCNLP 2021}, title={Argument
Undermining: Counter-Argument Generation by Attacking Weak Premises}, DOI={10.18653/v1/2021.findings-acl.159},
booktitle={Proceedings of the Joint Conference of the 59th Annual Meeting of the
Association for Computational Linguistics and the 11th International Joint Conference
on Natural Language Processing (ACL-IJCNLP 2021)}, publisher={Association for
Computational Linguistics}, author={Alshomary, Milad and Syed, Shahbaz and Potthast,
Martin and Wachsmuth, Henning}, year={2021}, pages={1816–1827}, collection={Findings
of the Association for Computational Linguistics: ACL-IJCNLP 2021} }'
chicago: 'Alshomary, Milad, Shahbaz Syed, Martin Potthast, and Henning Wachsmuth.
“Argument Undermining: Counter-Argument Generation by Attacking Weak Premises.”
In Proceedings of the Joint Conference of the 59th Annual Meeting of the Association
for Computational Linguistics and the 11th International Joint Conference on Natural
Language Processing (ACL-IJCNLP 2021), 1816–1827. Findings of the Association
for Computational Linguistics: ACL-IJCNLP 2021. Association for Computational
Linguistics, 2021. https://doi.org/10.18653/v1/2021.findings-acl.159.'
ieee: 'M. Alshomary, S. Syed, M. Potthast, and H. Wachsmuth, “Argument Undermining:
Counter-Argument Generation by Attacking Weak Premises,” in Proceedings of
the Joint Conference of the 59th Annual Meeting of the Association for Computational
Linguistics and the 11th International Joint Conference on Natural Language Processing
(ACL-IJCNLP 2021), Online, 2021, pp. 1816–1827, doi: 10.18653/v1/2021.findings-acl.159.'
mla: 'Alshomary, Milad, et al. “Argument Undermining: Counter-Argument Generation
by Attacking Weak Premises.” Proceedings of the Joint Conference of the 59th
Annual Meeting of the Association for Computational Linguistics and the 11th International
Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), Association
for Computational Linguistics, 2021, pp. 1816–1827, doi:10.18653/v1/2021.findings-acl.159.'
short: 'M. Alshomary, S. Syed, M. Potthast, H. Wachsmuth, in: Proceedings of the
Joint Conference of the 59th Annual Meeting of the Association for Computational
Linguistics and the 11th International Joint Conference on Natural Language Processing
(ACL-IJCNLP 2021), Association for Computational Linguistics, 2021, pp. 1816–1827.'
conference:
location: Online
name: The Joint Conference of the 59th Annual Meeting of the Association for Computational
Linguistics and the 11th International Joint Conference on Natural Language Processing
(ACL-IJCNLP 2021)
date_created: 2021-05-26T07:06:18Z
date_updated: 2022-05-09T15:06:36Z
department:
- _id: '600'
doi: 10.18653/v1/2021.findings-acl.159
language:
- iso: eng
main_file_link:
- url: https://aclanthology.org/2021.findings-acl.159.pdf
page: 1816–1827
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 Joint Conference of the 59th Annual Meeting of the
Association for Computational Linguistics and the 11th International Joint Conference
on Natural Language Processing (ACL-IJCNLP 2021)
publisher: Association for Computational Linguistics
series_title: 'Findings of the Association for Computational Linguistics: ACL-IJCNLP
2021'
status: public
title: 'Argument Undermining: Counter-Argument Generation by Attacking Weak Premises'
type: conference
user_id: '82920'
year: '2021'
...
---
_id: '45788'
author:
- first_name: Jonas
full_name: Bülling, Jonas
last_name: Bülling
citation:
ama: 'Bülling J. Political Speaker Transfer: Learning to Generate Text in the
Styles of Barack Obama and Donald Trump.; 2021.'
apa: 'Bülling, J. (2021). Political Speaker Transfer: Learning to Generate Text
in the Styles of Barack Obama and Donald Trump.'
bibtex: '@book{Bülling_2021, title={Political Speaker Transfer: Learning to Generate
Text in the Styles of Barack Obama and Donald Trump}, author={Bülling, Jonas},
year={2021} }'
chicago: 'Bülling, Jonas. Political Speaker Transfer: Learning to Generate Text
in the Styles of Barack Obama and Donald Trump, 2021.'
ieee: 'J. Bülling, Political Speaker Transfer: Learning to Generate Text in the
Styles of Barack Obama and Donald Trump. 2021.'
mla: 'Bülling, Jonas. Political Speaker Transfer: Learning to Generate Text in
the Styles of Barack Obama and Donald Trump. 2021.'
short: 'J. Bülling, Political Speaker Transfer: Learning to Generate Text in the
Styles of Barack Obama and Donald Trump, 2021.'
date_created: 2023-06-27T12:54:30Z
date_updated: 2023-07-05T07:32:18Z
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: 'Political Speaker Transfer: Learning to Generate Text in the Styles of Barack
Obama and Donald Trump'
type: mastersthesis
user_id: '477'
year: '2021'
...