---
_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: '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: '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: '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: '17347'
abstract:
- lang: eng
text: Peer-to-Peer news portals allow Internet users to write news articles and
make them available online to interested readers. Despite the fact that authors
are free in their choice of topics, there are a number of quality characteristics
that an article must meet before it is published. In addition to meaningful titles,
comprehensibly written texts and meaning- ful images, relevant tags are an important
criteria for the quality of such news. In this case study, we discuss the challenges
and common mistakes that Peer-to-Peer reporters face when tagging news and how
incorrect information can be corrected through the orchestration of existing Natu-
ral Language Processing services. Lastly, we use this illustrative example to
give insight into the challenges of dealing with bottom-up taxonomies.
author:
- first_name: Frederik Simon
full_name: Bäumer, Frederik Simon
id: '38837'
last_name: Bäumer
- first_name: Joschka
full_name: Kersting, Joschka
id: '58701'
last_name: Kersting
- first_name: Bianca
full_name: Buff, Bianca
last_name: Buff
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
citation:
ama: 'Bäumer FS, Kersting J, Buff B, Geierhos M. Tag Me If You Can: Insights into
the Challenges of Supporting Unrestricted P2P News Tagging. In: Audrius L, Rita
B, Daina G, Vilma S, eds. Information and Software Technologies. Vol 1283.
Communications in Computer and Information Science. Springer; 2020:368--382. doi:https://doi.org/10.1007/978-3-030-59506-7_30'
apa: 'Bäumer, F. S., Kersting, J., Buff, B., & Geierhos, M. (2020). Tag Me If
You Can: Insights into the Challenges of Supporting Unrestricted P2P News Tagging.
In L. Audrius, B. Rita, G. Daina, & S. Vilma (Eds.), Information and Software
Technologies (Vol. 1283, pp. 368--382). Kaunas, Litauen: Springer. https://doi.org/10.1007/978-3-030-59506-7_30'
bibtex: '@inbook{Bäumer_Kersting_Buff_Geierhos_2020, series={Communications in Computer
and Information Science}, title={Tag Me If You Can: Insights into the Challenges
of Supporting Unrestricted P2P News Tagging}, volume={1283}, DOI={https://doi.org/10.1007/978-3-030-59506-7_30},
booktitle={Information and Software Technologies}, publisher={Springer}, author={Bäumer,
Frederik Simon and Kersting, Joschka and Buff, Bianca and Geierhos, Michaela},
editor={Audrius, Lopata and Rita, Butkienė and Daina, Gudonienė and Vilma, SukackėEditors},
year={2020}, pages={368--382}, collection={Communications in Computer and Information
Science} }'
chicago: 'Bäumer, Frederik Simon, Joschka Kersting, Bianca Buff, and Michaela Geierhos.
“Tag Me If You Can: Insights into the Challenges of Supporting Unrestricted P2P
News Tagging.” In Information and Software Technologies, edited by Lopata
Audrius, Butkienė Rita, Gudonienė Daina, and Sukackė Vilma, 1283:368--382. Communications
in Computer and Information Science. Springer, 2020. https://doi.org/10.1007/978-3-030-59506-7_30.'
ieee: 'F. S. Bäumer, J. Kersting, B. Buff, and M. Geierhos, “Tag Me If You Can:
Insights into the Challenges of Supporting Unrestricted P2P News Tagging,” in
Information and Software Technologies, vol. 1283, L. Audrius, B. Rita,
G. Daina, and S. Vilma, Eds. Springer, 2020, pp. 368--382.'
mla: 'Bäumer, Frederik Simon, et al. “Tag Me If You Can: Insights into the Challenges
of Supporting Unrestricted P2P News Tagging.” Information and Software Technologies,
edited by Lopata Audrius et al., vol. 1283, Springer, 2020, pp. 368--382, doi:https://doi.org/10.1007/978-3-030-59506-7_30.'
short: 'F.S. Bäumer, J. Kersting, B. Buff, M. Geierhos, in: L. Audrius, B. Rita,
G. Daina, S. Vilma (Eds.), Information and Software Technologies, Springer, 2020,
pp. 368--382.'
conference:
end_date: 2020-10-17
location: Kaunas, Litauen
name: 26th International Conference on Information and Software Technologies (ICIST
2020)
start_date: 2020-10-15
date_created: 2020-06-26T14:23:52Z
date_updated: 2022-01-06T06:53:08Z
ddc:
- '004'
department:
- _id: '579'
- _id: '1'
- _id: '36'
doi: https://doi.org/10.1007/978-3-030-59506-7_30
editor:
- first_name: Lopata
full_name: Audrius, Lopata
last_name: Audrius
- first_name: Butkienė
full_name: Rita, Butkienė
last_name: Rita
- first_name: Gudonienė
full_name: Daina, Gudonienė
last_name: Daina
- first_name: Sukackė
full_name: Vilma, Sukackė
last_name: Vilma
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2020-11-07T19:47:30Z
date_updated: 2020-11-07T19:47:30Z
file_id: '20309'
file_name: Bäumer et al. (2020), Baeumer2020.pdf .pdf
file_size: 599881
relation: main_file
success: 1
file_date_updated: 2020-11-07T19:47:30Z
has_accepted_license: '1'
intvolume: ' 1283'
language:
- iso: eng
page: 368--382
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '9'
name: SFB 901 - Subproject B1
publication: Information and Software Technologies
publication_status: published
publisher: Springer
series_title: Communications in Computer and Information Science
status: public
title: 'Tag Me If You Can: Insights into the Challenges of Supporting Unrestricted
P2P News Tagging'
type: book_chapter
user_id: '58701'
volume: 1283
year: '2020'
...
---
_id: '18686'
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. SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED
APPROACH. In: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING
2020. IADIS; 2020:119--123.'
apa: 'Kersting, J., & Bäumer, F. S. (2020). SEMANTIC TAGGING OF REQUIREMENT
DESCRIPTIONS: A TRANSFORMER-BASED APPROACH. PROCEEDINGS OF THE INTERNATIONAL
CONFERENCE ON APPLIED COMPUTING 2020, 119--123.'
bibtex: '@inproceedings{Kersting_Bäumer_2020, title={SEMANTIC TAGGING OF REQUIREMENT
DESCRIPTIONS: A TRANSFORMER-BASED APPROACH}, booktitle={PROCEEDINGS OF THE INTERNATIONAL
CONFERENCE ON APPLIED COMPUTING 2020}, publisher={IADIS}, author={Kersting, Joschka
and Bäumer, Frederik Simon}, year={2020}, pages={119--123} }'
chicago: 'Kersting, Joschka, and Frederik Simon Bäumer. “SEMANTIC TAGGING OF REQUIREMENT
DESCRIPTIONS: A TRANSFORMER-BASED APPROACH.” In PROCEEDINGS OF THE INTERNATIONAL
CONFERENCE ON APPLIED COMPUTING 2020, 119--123. IADIS, 2020.'
ieee: 'J. Kersting and F. S. Bäumer, “SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS:
A TRANSFORMER-BASED APPROACH,” in PROCEEDINGS OF THE INTERNATIONAL CONFERENCE
ON APPLIED COMPUTING 2020, Lisbon, Portugal, 2020, pp. 119--123.'
mla: 'Kersting, Joschka, and Frederik Simon Bäumer. “SEMANTIC TAGGING OF REQUIREMENT
DESCRIPTIONS: A TRANSFORMER-BASED APPROACH.” PROCEEDINGS OF THE INTERNATIONAL
CONFERENCE ON APPLIED COMPUTING 2020, IADIS, 2020, pp. 119--123.'
short: 'J. Kersting, F.S. Bäumer, in: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE
ON APPLIED COMPUTING 2020, IADIS, 2020, pp. 119--123.'
conference:
end_date: 20.11.2020
location: Lisbon, Portugal
name: 17th International Conference on Applied Computing
start_date: 18.11.2020
date_created: 2020-08-31T10:59:54Z
date_updated: 2022-01-06T06:53:51Z
ddc:
- '000'
department:
- _id: '579'
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2020-11-19T17:29:03Z
date_updated: 2020-11-19T17:29:03Z
file_id: '20443'
file_name: Kersting & Bäumer (2020), Kersting2020d.pdf
file_size: 1064877
relation: main_file
success: 1
file_date_updated: 2020-11-19T17:29:03Z
has_accepted_license: '1'
keyword:
- Software Requirements
- Natural Language Processing
- Transfer Learning
- On-The-Fly Computing
language:
- iso: eng
page: 119--123
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 CONFERENCE ON APPLIED COMPUTING 2020
publisher: IADIS
status: public
title: 'SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH'
type: conference
user_id: '58701'
year: '2020'
...
---
_id: '15580'
abstract:
- lang: eng
text: This paper deals with aspect phrase extraction and classification in sentiment
analysis. We summarize current approaches and datasets from the domain of aspect-based
sentiment analysis. This domain detects sentiments expressed for individual aspects
in unstructured text data. So far, mainly commercial user reviews for products
or services such as restaurants were investigated. We here present our dataset
consisting of German physician reviews, a sensitive and linguistically complex
field. Furthermore, we describe the annotation process of a dataset for supervised
learning with neural networks. Moreover, we introduce our model for extracting
and classifying aspect phrases in one step, which obtains an F1-score of 80%.
By applying it to a more complex domain, our approach and results outperform previous
approaches.
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. Aspect Phrase Extraction in Sentiment Analysis with
Deep Learning. In: Proceedings of the 12th International Conference on Agents
and Artificial Intelligence (ICAART 2020) -- Special Session on Natural Language
Processing in Artificial Intelligence (NLPinAI 2020). Setúbal, Portugal: SCITEPRESS;
2020:391--400.'
apa: 'Kersting, J., & Geierhos, M. (2020). Aspect Phrase Extraction in Sentiment
Analysis with Deep Learning. In Proceedings of the 12th International Conference
on Agents and Artificial Intelligence (ICAART 2020) -- Special Session on Natural
Language Processing in Artificial Intelligence (NLPinAI 2020) (pp. 391--400).
Setúbal, Portugal: SCITEPRESS.'
bibtex: '@inproceedings{Kersting_Geierhos_2020, place={Setúbal, Portugal}, title={Aspect
Phrase Extraction in Sentiment Analysis with Deep Learning}, booktitle={Proceedings
of the 12th International Conference on Agents and Artificial Intelligence (ICAART
2020) -- Special Session on Natural Language Processing in Artificial Intelligence
(NLPinAI 2020)}, publisher={SCITEPRESS}, author={Kersting, Joschka and Geierhos,
Michaela}, year={2020}, pages={391--400} }'
chicago: 'Kersting, Joschka, and Michaela Geierhos. “Aspect Phrase Extraction in
Sentiment Analysis with Deep Learning.” In Proceedings of the 12th International
Conference on Agents and Artificial Intelligence (ICAART 2020) -- Special Session
on Natural Language Processing in Artificial Intelligence (NLPinAI 2020),
391--400. Setúbal, Portugal: SCITEPRESS, 2020.'
ieee: J. Kersting and M. Geierhos, “Aspect Phrase Extraction in Sentiment Analysis
with Deep Learning,” in Proceedings of the 12th International Conference on
Agents and Artificial Intelligence (ICAART 2020) -- Special Session on Natural
Language Processing in Artificial Intelligence (NLPinAI 2020), Valetta, Malta,
2020, pp. 391--400.
mla: Kersting, Joschka, and Michaela Geierhos. “Aspect Phrase Extraction in Sentiment
Analysis with Deep Learning.” Proceedings of the 12th International Conference
on Agents and Artificial Intelligence (ICAART 2020) -- Special Session on Natural
Language Processing in Artificial Intelligence (NLPinAI 2020), SCITEPRESS,
2020, pp. 391--400.
short: 'J. Kersting, M. Geierhos, in: Proceedings of the 12th International Conference
on Agents and Artificial Intelligence (ICAART 2020) -- Special Session on Natural
Language Processing in Artificial Intelligence (NLPinAI 2020), SCITEPRESS, Setúbal,
Portugal, 2020, pp. 391--400.'
conference:
location: Valetta, Malta
name: International Conference on Agents and Artificial Intelligence (ICAART) -- Special
Session on Natural Language Processing in Artificial Intelligence (NLPinAI)
date_created: 2020-01-15T08:35:07Z
date_updated: 2022-01-06T06:52:29Z
ddc:
- '000'
department:
- _id: '579'
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2020-09-18T09:27:00Z
date_updated: 2020-09-18T09:27:00Z
file_id: '19576'
file_name: Kersting & Geierhos (2020), Kersting2020.pdf
file_size: 421780
relation: main_file
success: 1
file_date_updated: 2020-09-18T09:27:00Z
has_accepted_license: '1'
keyword:
- Deep Learning
- Natural Language Processing
- Aspect-based Sentiment Analysis
language:
- iso: eng
page: 391--400
place: Setúbal, Portugal
project:
- _id: '3'
name: SFB 901 - Project Area B
- _id: '1'
name: SFB 901
- _id: '9'
name: SFB 901 - Subproject B1
publication: Proceedings of the 12th International Conference on Agents and Artificial
Intelligence (ICAART 2020) -- Special Session on Natural Language Processing in
Artificial Intelligence (NLPinAI 2020)
publisher: SCITEPRESS
status: public
title: Aspect Phrase Extraction in Sentiment Analysis with Deep Learning
type: conference
user_id: '58701'
year: '2020'
...
---
_id: '15582'
abstract:
- lang: eng
text: When it comes to increased digitization in the health care domain, privacy
is a relevant topic nowadays. This relates to patient data, electronic health
records or physician reviews published online, for instance. There exist different
approaches to the protection of individuals’ privacy, which focus on the anonymization
and masking of personal information subsequent to their mining. In the medical
domain in particular, measures to protect the privacy of patients are of high
importance due to the amount of sensitive data that is involved (e.g. age, gender,
illnesses, medication). While privacy breaches in structured data can be detected
more easily, disclosure in written texts is more difficult to find automatically
due to the unstructured nature of natural language. Therefore, we take a detailed
look at existing research on areas related to privacy protection. Likewise, we
review approaches to the automatic detection of privacy disclosure in different
types of medical data. We provide a survey of several studies concerned with privacy
breaches in the medical domain with a focus on Physician Review Websites (PRWs).
Finally, we briefly develop implications and directions for further research.
author:
- first_name: Bianca
full_name: Buff, Bianca
last_name: Buff
- 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: 'Buff B, Kersting J, Geierhos M. Detection of Privacy Disclosure in the Medical
Domain: A Survey. In: Proceedings of the 9th International Conference on Pattern
Recognition Applications and Methods (ICPRAM 2020). Setúbal, Portugal: SCITEPRESS;
2020:630--637.'
apa: 'Buff, B., Kersting, J., & Geierhos, M. (2020). Detection of Privacy Disclosure
in the Medical Domain: A Survey. In Proceedings of the 9th International Conference
on Pattern Recognition Applications and Methods (ICPRAM 2020) (pp. 630--637).
Setúbal, Portugal: SCITEPRESS.'
bibtex: '@inproceedings{Buff_Kersting_Geierhos_2020, place={Setúbal, Portugal},
title={Detection of Privacy Disclosure in the Medical Domain: A Survey}, booktitle={Proceedings
of the 9th International Conference on Pattern Recognition Applications and Methods
(ICPRAM 2020)}, publisher={SCITEPRESS}, author={Buff, Bianca and Kersting, Joschka
and Geierhos, Michaela}, year={2020}, pages={630--637} }'
chicago: 'Buff, Bianca, Joschka Kersting, and Michaela Geierhos. “Detection of Privacy
Disclosure in the Medical Domain: A Survey.” In Proceedings of the 9th International
Conference on Pattern Recognition Applications and Methods (ICPRAM 2020),
630--637. Setúbal, Portugal: SCITEPRESS, 2020.'
ieee: 'B. Buff, J. Kersting, and M. Geierhos, “Detection of Privacy Disclosure in
the Medical Domain: A Survey,” in Proceedings of the 9th International Conference
on Pattern Recognition Applications and Methods (ICPRAM 2020), Valetta, Malta,
2020, pp. 630--637.'
mla: 'Buff, Bianca, et al. “Detection of Privacy Disclosure in the Medical Domain:
A Survey.” Proceedings of the 9th International Conference on Pattern Recognition
Applications and Methods (ICPRAM 2020), SCITEPRESS, 2020, pp. 630--637.'
short: 'B. Buff, J. Kersting, M. Geierhos, in: Proceedings of the 9th International
Conference on Pattern Recognition Applications and Methods (ICPRAM 2020), SCITEPRESS,
Setúbal, Portugal, 2020, pp. 630--637.'
conference:
location: Valetta, Malta
name: International Conference on Pattern Recognition Applications and Methods (ICPRAM)
date_created: 2020-01-15T08:49:25Z
date_updated: 2022-01-06T06:52:30Z
ddc:
- '000'
department:
- _id: '579'
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2020-09-18T09:25:30Z
date_updated: 2020-09-18T09:25:30Z
file_id: '19574'
file_name: Buff et al. (2020), Buff2020.pdf
file_size: 287956
relation: main_file
success: 1
file_date_updated: 2020-09-18T09:25:30Z
has_accepted_license: '1'
keyword:
- Identity Disclosure
- Privacy Protection
- Physician Review Website
- De-Anonymization
- Medical Domain
language:
- iso: eng
page: 630--637
place: Setúbal, Portugal
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 9th International Conference on Pattern Recognition
Applications and Methods (ICPRAM 2020)
publisher: SCITEPRESS
status: public
title: 'Detection of Privacy Disclosure in the Medical Domain: A Survey'
type: conference
user_id: '58701'
year: '2020'
...
---
_id: '15635'
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. Neural Learning for Aspect Phrase Extraction and Classification
in Sentiment Analysis. In: Proceedings of the 33rd International Florida Artificial
Intelligence Research Symposium (FLAIRS) Conference. North Miami Beach, FL,
USA: AAAI; 2020:282--285.'
apa: 'Kersting, J., & Geierhos, M. (2020). Neural Learning for Aspect Phrase
Extraction and Classification in Sentiment Analysis. In Proceedings of the
33rd International Florida Artificial Intelligence Research Symposium (FLAIRS)
Conference (pp. 282--285). North Miami Beach, FL, USA: AAAI.'
bibtex: '@inproceedings{Kersting_Geierhos_2020, place={North Miami Beach, FL, USA},
title={Neural Learning for Aspect Phrase Extraction and Classification in Sentiment
Analysis}, booktitle={Proceedings of the 33rd International Florida Artificial
Intelligence Research Symposium (FLAIRS) Conference}, publisher={AAAI}, author={Kersting,
Joschka and Geierhos, Michaela}, year={2020}, pages={282--285} }'
chicago: 'Kersting, Joschka, and Michaela Geierhos. “Neural Learning for Aspect
Phrase Extraction and Classification in Sentiment Analysis.” In Proceedings
of the 33rd International Florida Artificial Intelligence Research Symposium (FLAIRS)
Conference, 282--285. North Miami Beach, FL, USA: AAAI, 2020.'
ieee: J. Kersting and M. Geierhos, “Neural Learning for Aspect Phrase Extraction
and Classification in Sentiment Analysis,” in Proceedings of the 33rd International
Florida Artificial Intelligence Research Symposium (FLAIRS) Conference, North
Miami Beach, FL, USA, 2020, pp. 282--285.
mla: Kersting, Joschka, and Michaela Geierhos. “Neural Learning for Aspect Phrase
Extraction and Classification in Sentiment Analysis.” Proceedings of the 33rd
International Florida Artificial Intelligence Research Symposium (FLAIRS) Conference,
AAAI, 2020, pp. 282--285.
short: 'J. Kersting, M. Geierhos, in: Proceedings of the 33rd International Florida
Artificial Intelligence Research Symposium (FLAIRS) Conference, AAAI, North Miami
Beach, FL, USA, 2020, pp. 282--285.'
conference:
end_date: 2020-05-20
location: North Miami Beach, FL, USA
name: The 33rd International Florida Artificial Intelligence Research Symposium
(FLAIRS) Conference
start_date: 2020-05-17
date_created: 2020-01-24T09:10:09Z
date_updated: 2022-01-06T06:52:31Z
ddc:
- '000'
department:
- _id: '579'
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2020-09-18T09:39:08Z
date_updated: 2020-09-18T09:39:08Z
file_id: '19582'
file_name: Kersting & Geierhos (2020b), Kersting2020b.pdf
file_size: 464976
relation: main_file
success: 1
file_date_updated: 2020-09-18T09:39:08Z
has_accepted_license: '1'
language:
- iso: eng
page: 282--285
place: North Miami Beach, FL, USA
project:
- _id: '3'
name: SFB 901 - Project Area B
- _id: '9'
name: SFB 901 - Subproject B1
- _id: '1'
name: SFB 901
publication: Proceedings of the 33rd International Florida Artificial Intelligence
Research Symposium (FLAIRS) Conference
publisher: AAAI
status: public
title: Neural Learning for Aspect Phrase Extraction and Classification in Sentiment
Analysis
type: conference
user_id: '58701'
year: '2020'
...
---
_id: '15256'
abstract:
- lang: eng
text: This paper deals with online customer reviews of local multi-service providers.
While many studies investigate product reviews and online labour markets with
service providers delivering intangible products “over the wire”, we focus on
websites where providers offer multiple distinct services that can be booked,
paid and reviewed online but are performed locally offline. This type of service
providers has so far been neglected in the literature. This paper analyses reviews
and applies sentiment analysis. It aims to gain new insights into local multi-service
providers’ performance. There is a broad literature range presented with regard
to the topics addressed. The results show, among other things, that providers
with good ratings continue to perform well over time. We find that many positive
reviews seem to encourage sales. On average, quantitative star ratings and qualitative
ratings in the form of review texts match. Further results are also achieved in
this study.
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. What Reviews in Local Online Labour Markets Reveal
about the Performance of Multi-Service Providers. In: Proceedings of the 9th
International Conference on Pattern Recognition Applications and Methods.
Setúbal, Portugal: SCITEPRESS; 2020:263--272.'
apa: 'Kersting, J., & Geierhos, M. (2020). What Reviews in Local Online Labour
Markets Reveal about the Performance of Multi-Service Providers. In Proceedings
of the 9th International Conference on Pattern Recognition Applications and Methods
(pp. 263--272). Setúbal, Portugal: SCITEPRESS.'
bibtex: '@inproceedings{Kersting_Geierhos_2020, place={Setúbal, Portugal}, title={What
Reviews in Local Online Labour Markets Reveal about the Performance of Multi-Service
Providers}, booktitle={Proceedings of the 9th International Conference on Pattern
Recognition Applications and Methods}, publisher={SCITEPRESS}, author={Kersting,
Joschka and Geierhos, Michaela}, year={2020}, pages={263--272} }'
chicago: 'Kersting, Joschka, and Michaela Geierhos. “What Reviews in Local Online
Labour Markets Reveal about the Performance of Multi-Service Providers.” In Proceedings
of the 9th International Conference on Pattern Recognition Applications and Methods,
263--272. Setúbal, Portugal: SCITEPRESS, 2020.'
ieee: J. Kersting and M. Geierhos, “What Reviews in Local Online Labour Markets
Reveal about the Performance of Multi-Service Providers,” in Proceedings of
the 9th International Conference on Pattern Recognition Applications and Methods,
Valetta, Malta, 2020, pp. 263--272.
mla: Kersting, Joschka, and Michaela Geierhos. “What Reviews in Local Online Labour
Markets Reveal about the Performance of Multi-Service Providers.” Proceedings
of the 9th International Conference on Pattern Recognition Applications and Methods,
SCITEPRESS, 2020, pp. 263--272.
short: 'J. Kersting, M. Geierhos, in: Proceedings of the 9th International Conference
on Pattern Recognition Applications and Methods, SCITEPRESS, Setúbal, Portugal,
2020, pp. 263--272.'
conference:
location: Valetta, Malta
name: International Conference on Pattern Recognition Applications and Methods (ICPRAM)
date_created: 2019-12-06T13:09:42Z
date_updated: 2022-01-06T06:52:19Z
ddc:
- '000'
department:
- _id: '579'
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2020-09-18T09:27:41Z
date_updated: 2020-09-18T09:27:41Z
file_id: '19577'
file_name: Kersting & Geierhos (2020c), Kersting2020c.pdf
file_size: 963370
relation: main_file
success: 1
file_date_updated: 2020-09-18T09:27:41Z
has_accepted_license: '1'
keyword:
- Customer Reviews
- Sentiment Analysis
- Online Labour Markets
language:
- iso: eng
page: 263--272
place: Setúbal, Portugal
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 9th International Conference on Pattern Recognition
Applications and Methods
publisher: SCITEPRESS
status: public
title: What Reviews in Local Online Labour Markets Reveal about the Performance of
Multi-Service Providers
type: conference
user_id: '58701'
year: '2020'
...
---
_id: '8312'
author:
- first_name: Frederik Simon
full_name: Bäumer, Frederik Simon
id: '38837'
last_name: Bäumer
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
citation:
ama: 'Bäumer FS, Geierhos M. Requirements Engineering in OTF-Computing. In: Encyclopedia.Pub.
Basel, Switzerland: MDPI; 2019.'
apa: 'Bäumer, F. S., & Geierhos, M. (2019). Requirements Engineering in OTF-Computing.
In encyclopedia.pub. Basel, Switzerland: MDPI.'
bibtex: '@inbook{Bäumer_Geierhos_2019, place={Basel, Switzerland}, title={Requirements
Engineering in OTF-Computing}, booktitle={encyclopedia.pub}, publisher={MDPI},
author={Bäumer, Frederik Simon and Geierhos, Michaela}, year={2019} }'
chicago: 'Bäumer, Frederik Simon, and Michaela Geierhos. “Requirements Engineering
in OTF-Computing.” In Encyclopedia.Pub. Basel, Switzerland: MDPI, 2019.'
ieee: 'F. S. Bäumer and M. Geierhos, “Requirements Engineering in OTF-Computing,”
in encyclopedia.pub, Basel, Switzerland: MDPI, 2019.'
mla: Bäumer, Frederik Simon, and Michaela Geierhos. “Requirements Engineering in
OTF-Computing.” Encyclopedia.Pub, MDPI, 2019.
short: 'F.S. Bäumer, M. Geierhos, in: Encyclopedia.Pub, MDPI, Basel, Switzerland,
2019.'
date_created: 2019-03-05T08:54:37Z
date_updated: 2022-01-06T07:03:53Z
department:
- _id: '36'
- _id: '1'
- _id: '579'
keyword:
- OTF Computing
- Natural Language Processing
- Requirements Engineering
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://encyclopedia.pub/131
oa: '1'
place: Basel, Switzerland
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '9'
name: SFB 901 - Subproject B1
publication: encyclopedia.pub
publication_status: published
publisher: MDPI
quality_controlled: '1'
status: public
title: Requirements Engineering in OTF-Computing
type: encyclopedia_article
user_id: '42496'
year: '2019'
...
---
_id: '8424'
abstract:
- lang: eng
text: 'The vision of On-the-Fly (OTF) Computing is to compose and provide software
services ad hoc, based on requirement descriptions in natural language. Since
non-technical users write their software requirements themselves and in unrestricted
natural language, deficits occur such as inaccuracy and incompleteness. These
deficits are usually met by natural language processing methods, which have to
face special challenges in OTF Computing because maximum automation is the goal.
In this paper, we present current automatic approaches for solving inaccuracies
and incompletenesses in natural language requirement descriptions and elaborate
open challenges. In particular, we will discuss the necessity of domain-specific
resources and show why, despite far-reaching automation, an intelligent and guided
integration of end users into the compensation process is required. In this context,
we present our idea of a chat bot that integrates users into the compensation
process depending on the given circumstances. '
article_number: '22'
article_type: original
author:
- first_name: Frederik Simon
full_name: Bäumer, Frederik Simon
id: '38837'
last_name: Bäumer
- 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: 'Bäumer FS, Kersting J, Geierhos M. Natural Language Processing in OTF Computing:
Challenges and the Need for Interactive Approaches. Computers. 2019;8(1).
doi:10.3390/computers8010022'
apa: 'Bäumer, F. S., Kersting, J., & Geierhos, M. (2019). Natural Language Processing
in OTF Computing: Challenges and the Need for Interactive Approaches. Computers,
8(1). https://doi.org/10.3390/computers8010022'
bibtex: '@article{Bäumer_Kersting_Geierhos_2019, title={Natural Language Processing
in OTF Computing: Challenges and the Need for Interactive Approaches}, volume={8},
DOI={10.3390/computers8010022},
number={122}, journal={Computers}, publisher={MDPI AG, Basel, Switzerland}, author={Bäumer,
Frederik Simon and Kersting, Joschka and Geierhos, Michaela}, year={2019} }'
chicago: 'Bäumer, Frederik Simon, Joschka Kersting, and Michaela Geierhos. “Natural
Language Processing in OTF Computing: Challenges and the Need for Interactive
Approaches.” Computers 8, no. 1 (2019). https://doi.org/10.3390/computers8010022.'
ieee: 'F. S. Bäumer, J. Kersting, and M. Geierhos, “Natural Language Processing
in OTF Computing: Challenges and the Need for Interactive Approaches,” Computers,
vol. 8, no. 1, 2019.'
mla: 'Bäumer, Frederik Simon, et al. “Natural Language Processing in OTF Computing:
Challenges and the Need for Interactive Approaches.” Computers, vol. 8,
no. 1, 22, MDPI AG, Basel, Switzerland, 2019, doi:10.3390/computers8010022.'
short: F.S. Bäumer, J. Kersting, M. Geierhos, Computers 8 (2019).
conference:
end_date: 2018-10-06
location: Vilnius, Lithuania
name: 24th International Conference on Information and Software Technologies (ICIST
2018)
start_date: 2018-10-04
date_created: 2019-03-06T14:27:28Z
date_updated: 2022-01-06T07:03:55Z
ddc:
- '000'
department:
- _id: '36'
- _id: '1'
- _id: '579'
doi: 10.3390/computers8010022
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2020-09-18T09:23:34Z
date_updated: 2020-09-18T09:23:34Z
file_id: '19572'
file_name: Bäumer et al. (2019), Baeumer2019.pdf
file_size: 3164523
relation: main_file
success: 1
file_date_updated: 2020-09-18T09:23:34Z
has_accepted_license: '1'
intvolume: ' 8'
issue: '1'
keyword:
- Inaccuracy Detection
- Natural Language Software Requirements
- Chat Bot
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.mdpi.com/2073-431X/8/1/22/pdf
oa: '1'
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '9'
name: SFB 901 - Subproject B1
publication: Computers
publication_identifier:
issn:
- 2073-431X
publication_status: published
publisher: MDPI AG, Basel, Switzerland
quality_controlled: '1'
status: public
title: 'Natural Language Processing in OTF Computing: Challenges and the Need for
Interactive Approaches'
type: journal_article
user_id: '58701'
volume: 8
year: '2019'
...
---
_id: '8529'
author:
- first_name: Nina
full_name: Seemann, Nina
id: '65408'
last_name: Seemann
- first_name: Marie-Luis
full_name: Merten, Marie-Luis
last_name: Merten
citation:
ama: 'Seemann N, Merten M-L. UPB-Annotate: Ein maßgeschneidertes Toolkit für historische
Texte. In: Sahle P, ed. DHd 2019 Digital Humanities: multimedial & multimodal.
Konferenzabstracts. Frankfurt am Main, Germany: Zenodo; 2019:352-353. doi:10.5281/ZENODO.2596094'
apa: 'Seemann, N., & Merten, M.-L. (2019). UPB-Annotate: Ein maßgeschneidertes
Toolkit für historische Texte. In P. Sahle (Ed.), DHd 2019 Digital Humanities:
multimedial & multimodal. Konferenzabstracts (pp. 352–353). Frankfurt
am Main, Germany: Zenodo. https://doi.org/10.5281/ZENODO.2596094'
bibtex: '@inproceedings{Seemann_Merten_2019, place={Frankfurt am Main, Germany},
title={UPB-Annotate: Ein maßgeschneidertes Toolkit für historische Texte}, DOI={10.5281/ZENODO.2596094}, booktitle={DHd
2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts}, publisher={Zenodo},
author={Seemann, Nina and Merten, Marie-Luis}, editor={Sahle, PatrickEditor},
year={2019}, pages={352–353} }'
chicago: 'Seemann, Nina, and Marie-Luis Merten. “UPB-Annotate: Ein maßgeschneidertes
Toolkit für historische Texte.” In DHd 2019 Digital Humanities: multimedial
& multimodal. Konferenzabstracts, edited by Patrick Sahle, 352–53. Frankfurt
am Main, Germany: Zenodo, 2019. https://doi.org/10.5281/ZENODO.2596094.'
ieee: 'N. Seemann and M.-L. Merten, “UPB-Annotate: Ein maßgeschneidertes Toolkit
für historische Texte,” in DHd 2019 Digital Humanities: multimedial &
multimodal. Konferenzabstracts, Mainz and Frankfurt am Main, Germany, 2019,
pp. 352–353.'
mla: 'Seemann, Nina, and Marie-Luis Merten. “UPB-Annotate: Ein maßgeschneidertes
Toolkit für historische Texte.” DHd 2019 Digital Humanities: multimedial &
multimodal. Konferenzabstracts, edited by Patrick Sahle, Zenodo, 2019, pp.
352–53, doi:10.5281/ZENODO.2596094.'
short: 'N. Seemann, M.-L. Merten, in: P. Sahle (Ed.), DHd 2019 Digital Humanities:
multimedial & multimodal. Konferenzabstracts, Zenodo, Frankfurt am Main, Germany,
2019, pp. 352–353.'
conference:
end_date: 2019-03-29
location: Mainz and Frankfurt am Main, Germany
name: 'DHd 2019 Digital Humanities: multimedial & multimodal.'
start_date: 2019-03-25
date_created: 2019-03-21T08:39:17Z
date_updated: 2022-01-06T07:03:56Z
department:
- _id: '36'
- _id: '1'
- _id: '579'
doi: 10.5281/ZENODO.2596094
editor:
- first_name: Patrick
full_name: Sahle, Patrick
last_name: Sahle
language:
- iso: ger
main_file_link:
- open_access: '1'
url: https://zenodo.org/record/2596095/files/2019_DHd_BookOfAbstracts_web.pdf?download=1
oa: '1'
page: 352-353
place: Frankfurt am Main, Germany
project:
- _id: '39'
name: InterGramm
publication: 'DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts'
publication_identifier:
isbn:
- 978-3-00-062166-6
publication_status: published
publisher: Zenodo
status: public
title: 'UPB-Annotate: Ein maßgeschneidertes Toolkit für historische Texte'
type: conference_abstract
user_id: '13929'
year: '2019'
...
---
_id: '8532'
author:
- first_name: Frederik Simon
full_name: Bäumer, Frederik Simon
id: '38837'
last_name: Bäumer
- first_name: Bianca
full_name: Buff, Bianca
last_name: Buff
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
citation:
ama: 'Bäumer FS, Buff B, Geierhos M. Potentielle Privatsphäreverletzungen aufdecken
und automatisiert sichtbar machen. In: Sahle P, ed. DHd 2019 Digital Humanities:
multimedial & multimodal. Konferenzabstracts. Frankfurt am Main, Germany:
Zenodo; 2019:192-193. doi:10.5281/zenodo.2596095'
apa: 'Bäumer, F. S., Buff, B., & Geierhos, M. (2019). Potentielle Privatsphäreverletzungen
aufdecken und automatisiert sichtbar machen. In P. Sahle (Ed.), DHd 2019 Digital
Humanities: multimedial & multimodal. Konferenzabstracts (pp. 192–193).
Frankfurt am Main, Germany: Zenodo. https://doi.org/10.5281/zenodo.2596095'
bibtex: '@inproceedings{Bäumer_Buff_Geierhos_2019, place={Frankfurt am Main, Germany},
title={Potentielle Privatsphäreverletzungen aufdecken und automatisiert sichtbar
machen}, DOI={10.5281/zenodo.2596095},
booktitle={DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts},
publisher={Zenodo}, author={Bäumer, Frederik Simon and Buff, Bianca and Geierhos,
Michaela}, editor={Sahle, PatrickEditor}, year={2019}, pages={192–193} }'
chicago: 'Bäumer, Frederik Simon, Bianca Buff, and Michaela Geierhos. “Potentielle
Privatsphäreverletzungen aufdecken und automatisiert sichtbar machen.” In DHd
2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts,
edited by Patrick Sahle, 192–93. Frankfurt am Main, Germany: Zenodo, 2019. https://doi.org/10.5281/zenodo.2596095.'
ieee: 'F. S. Bäumer, B. Buff, and M. Geierhos, “Potentielle Privatsphäreverletzungen
aufdecken und automatisiert sichtbar machen,” in DHd 2019 Digital Humanities:
multimedial & multimodal. Konferenzabstracts, Mainz and Frankfurt am Main,
Germany, 2019, pp. 192–193.'
mla: 'Bäumer, Frederik Simon, et al. “Potentielle Privatsphäreverletzungen aufdecken
und automatisiert sichtbar machen.” DHd 2019 Digital Humanities: multimedial
& multimodal. Konferenzabstracts, edited by Patrick Sahle, Zenodo, 2019,
pp. 192–93, doi:10.5281/zenodo.2596095.'
short: 'F.S. Bäumer, B. Buff, M. Geierhos, in: P. Sahle (Ed.), DHd 2019 Digital
Humanities: multimedial & multimodal. Konferenzabstracts, Zenodo, Frankfurt
am Main, Germany, 2019, pp. 192–193.'
conference:
end_date: 2019-03-29
location: Mainz and Frankfurt am Main, Germany
name: 'DHd 2019 Digital Humanities: multimedial & multimodal.'
start_date: 2019-03-25
date_created: 2019-03-21T09:02:37Z
date_updated: 2022-01-06T07:03:56Z
department:
- _id: '36'
- _id: '1'
- _id: '579'
doi: 10.5281/zenodo.2596095
editor:
- first_name: Patrick
full_name: Sahle, Patrick
last_name: Sahle
language:
- iso: ger
main_file_link:
- open_access: '1'
url: https://zenodo.org/record/2596095/files/2019_DHd_BookOfAbstracts_web.pdf?download=1
oa: '1'
page: 192-193
place: Frankfurt am Main, Germany
publication: 'DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts'
publication_identifier:
isbn:
- 978-3-00-062166-6
publication_status: published
publisher: Zenodo
status: public
title: Potentielle Privatsphäreverletzungen aufdecken und automatisiert sichtbar
machen
type: conference_abstract
user_id: '13929'
year: '2019'
...
---
_id: '9613'
abstract:
- lang: eng
text: The ability to openly evaluate products, locations and services is an achievement
of the Web 2.0. It has never been easier to inform oneself about the quality of
products or services and possible alternatives. Forming one’s own opinion based
on the impressions of other people can lead to better experiences. However, this
presupposes trust in one’s fellows as well as in the quality of the review platforms.
In previous work on physician reviews and the corresponding websites, it was observed
that there occurs faulty behavior by some reviewers and there were noteworthy
differences in the technical implementation of the portals and in the efforts
of site operators to maintain high quality reviews. These experiences raise new
questions regarding what trust means on review platforms, how trust arises and
how easily it can be destroyed.
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
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
citation:
ama: 'Kersting J, Bäumer FS, Geierhos M. In Reviews We Trust: But Should We? Experiences
with Physician Review Websites. In: Ramachandran M, Walters R, Wills G, Méndez
Muñoz V, Chang V, eds. Proceedings of the 4th International Conference on
Internet of Things, Big Data and Security. Setúbal, Portugal: SCITEPRESS;
2019:147-155.'
apa: 'Kersting, J., Bäumer, F. S., & Geierhos, M. (2019). In Reviews We Trust:
But Should We? Experiences with Physician Review Websites. In M. Ramachandran,
R. Walters, G. Wills, V. Méndez Muñoz, & V. Chang (Eds.), Proceedings
of the 4th International Conference on Internet of Things, Big Data and Security
(pp. 147–155). Setúbal, Portugal: SCITEPRESS.'
bibtex: '@inproceedings{Kersting_Bäumer_Geierhos_2019, place={Setúbal, Portugal},
title={In Reviews We Trust: But Should We? Experiences with Physician Review Websites},
booktitle={Proceedings of the 4th International Conference on Internet of Things,
Big Data and Security}, publisher={SCITEPRESS}, author={Kersting, Joschka and
Bäumer, Frederik Simon and Geierhos, Michaela}, editor={Ramachandran, Muthu and
Walters, Robert and Wills, Gary and Méndez Muñoz, Víctor and Chang, VictorEditors},
year={2019}, pages={147–155} }'
chicago: 'Kersting, Joschka, Frederik Simon Bäumer, and Michaela Geierhos. “In Reviews
We Trust: But Should We? Experiences with Physician Review Websites.” In Proceedings
of the 4th International Conference on Internet of Things, Big Data and Security,
edited by Muthu Ramachandran, Robert Walters, Gary Wills, Víctor Méndez Muñoz,
and Victor Chang, 147–55. Setúbal, Portugal: SCITEPRESS, 2019.'
ieee: 'J. Kersting, F. S. Bäumer, and M. Geierhos, “In Reviews We Trust: But Should
We? Experiences with Physician Review Websites,” in Proceedings of the 4th
International Conference on Internet of Things, Big Data and Security, Heraklion,
Greece, 2019, pp. 147–155.'
mla: 'Kersting, Joschka, et al. “In Reviews We Trust: But Should We? Experiences
with Physician Review Websites.” Proceedings of the 4th International Conference
on Internet of Things, Big Data and Security, edited by Muthu Ramachandran
et al., SCITEPRESS, 2019, pp. 147–55.'
short: 'J. Kersting, F.S. Bäumer, M. Geierhos, in: M. Ramachandran, R. Walters,
G. Wills, V. Méndez Muñoz, V. Chang (Eds.), Proceedings of the 4th International
Conference on Internet of Things, Big Data and Security, SCITEPRESS, Setúbal,
Portugal, 2019, pp. 147–155.'
conference:
end_date: 2019-05-04
location: Heraklion, Greece
name: 4th International Conference on Internet of Things, Big Data and Security
(IoTBDS 2019)
start_date: 2019-05-02
date_created: 2019-05-06T09:00:48Z
date_updated: 2022-01-06T07:04:17Z
ddc:
- '000'
department:
- _id: '1'
- _id: '579'
editor:
- first_name: Muthu
full_name: Ramachandran, Muthu
last_name: Ramachandran
- first_name: Robert
full_name: Walters, Robert
last_name: Walters
- first_name: Gary
full_name: Wills, Gary
last_name: Wills
- first_name: Víctor
full_name: Méndez Muñoz, Víctor
last_name: Méndez Muñoz
- first_name: Victor
full_name: Chang, Victor
last_name: Chang
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2020-09-18T09:24:41Z
date_updated: 2020-09-18T09:24:41Z
file_id: '19573'
file_name: Kersting et al. (2019), Kersting2019.pdf
file_size: 1112502
relation: main_file
success: 1
file_date_updated: 2020-09-18T09:24:41Z
has_accepted_license: '1'
keyword:
- Trust
- Physician Reviews
- Network Analysis
language:
- iso: eng
main_file_link:
- url: www.insticc.org/Primoris/Resources/PaperPdf.ashx?idPaper=77454
page: 147-155
place: Setúbal, Portugal
publication: Proceedings of the 4th International Conference on Internet of Things,
Big Data and Security
publication_identifier:
isbn:
- 978-989-758-369-8
unknown:
- 2184-4976
publication_status: published
publisher: SCITEPRESS
quality_controlled: '1'
status: public
title: 'In Reviews We Trust: But Should We? Experiences with Physician Review Websites'
type: conference
user_id: '58701'
year: '2019'
...
---
_id: '12946'
author:
- first_name: Frederik Simon
full_name: Bäumer, Frederik Simon
id: '38837'
last_name: Bäumer
- first_name: Bianca
full_name: Buff, Bianca
last_name: Buff
citation:
ama: 'Bäumer FS, Buff B. How to Boost Customer Relationship Management via Web Mining
Benefiting from the Glass Customer’s Openness. In: Proceedings of the 8th International
Conference on Data Science, Technology and Applications. ; 2019. doi:10.5220/0007828301290136'
apa: Bäumer, F. S., & Buff, B. (2019). How to Boost Customer Relationship Management
via Web Mining Benefiting from the Glass Customer’s Openness. In Proceedings
of the 8th International Conference on Data Science, Technology and Applications.
https://doi.org/10.5220/0007828301290136
bibtex: '@inproceedings{Bäumer_Buff_2019, title={How to Boost Customer Relationship
Management via Web Mining Benefiting from the Glass Customer’s Openness}, DOI={10.5220/0007828301290136},
booktitle={Proceedings of the 8th International Conference on Data Science, Technology
and Applications}, author={Bäumer, Frederik Simon and Buff, Bianca}, year={2019}
}'
chicago: Bäumer, Frederik Simon, and Bianca Buff. “How to Boost Customer Relationship
Management via Web Mining Benefiting from the Glass Customer’s Openness.” In Proceedings
of the 8th International Conference on Data Science, Technology and Applications,
2019. https://doi.org/10.5220/0007828301290136.
ieee: F. S. Bäumer and B. Buff, “How to Boost Customer Relationship Management via
Web Mining Benefiting from the Glass Customer’s Openness,” in Proceedings of
the 8th International Conference on Data Science, Technology and Applications,
2019.
mla: Bäumer, Frederik Simon, and Bianca Buff. “How to Boost Customer Relationship
Management via Web Mining Benefiting from the Glass Customer’s Openness.” Proceedings
of the 8th International Conference on Data Science, Technology and Applications,
2019, doi:10.5220/0007828301290136.
short: 'F.S. Bäumer, B. Buff, in: Proceedings of the 8th International Conference
on Data Science, Technology and Applications, 2019.'
date_created: 2019-08-19T08:26:42Z
date_updated: 2022-01-06T06:51:27Z
department:
- _id: '579'
- _id: '1'
doi: 10.5220/0007828301290136
language:
- iso: eng
publication: Proceedings of the 8th International Conference on Data Science, Technology
and Applications
publication_identifier:
isbn:
- '9789897583773'
publication_status: published
status: public
title: How to Boost Customer Relationship Management via Web Mining Benefiting from
the Glass Customer’s Openness
type: conference
user_id: '38837'
year: '2019'
...
---
_id: '13435'
author:
- first_name: Edwin
full_name: Friesen, Edwin
last_name: Friesen
citation:
ama: 'Friesen E. Requirements Engineering im OTF-Computing: Informationsextraktion
und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis.
Universität Paderborn; 2019.'
apa: 'Friesen, E. (2019). Requirements Engineering im OTF-Computing: Informationsextraktion
und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis.
Universität Paderborn.'
bibtex: '@book{Friesen_2019, title={Requirements Engineering im OTF-Computing: Informationsextraktion
und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis},
publisher={Universität Paderborn}, author={Friesen, Edwin}, year={2019} }'
chicago: 'Friesen, Edwin. Requirements Engineering im OTF-Computing: Informationsextraktion
und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis.
Universität Paderborn, 2019.'
ieee: 'E. Friesen, Requirements Engineering im OTF-Computing: Informationsextraktion
und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis.
Universität Paderborn, 2019.'
mla: 'Friesen, Edwin. Requirements Engineering im OTF-Computing: Informationsextraktion
und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis.
Universität Paderborn, 2019.'
short: 'E. Friesen, Requirements Engineering im OTF-Computing: Informationsextraktion
und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis, Universität
Paderborn, 2019.'
date_created: 2019-09-20T14:58:49Z
date_updated: 2022-01-06T06:51:36Z
department:
- _id: '36'
- _id: '1'
- _id: '579'
language:
- iso: ger
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '9'
name: SFB 901 - Subproject B1
publisher: Universität Paderborn
status: public
supervisor:
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
title: 'Requirements Engineering im OTF-Computing: Informationsextraktion und Unvollständigkeitskompensation
mittels domänenspezifischer Wissensbasis'
type: bachelorsthesis
user_id: '477'
year: '2019'
...
---
_id: '2322'
abstract:
- lang: eng
text: "The vision of On-The-Fly Computing is an automatic composition\r\nof existing
software services. Based on natural language software\r\ndescriptions, end users
will receive compositions tailored to their needs.\r\nFor this reason, the quality
of the initial software service description\r\nstrongly determines whether a software
composition really meets the expectations\r\nof end users. In this paper, we expose
open NLP challenges\r\nneeded to be faced for service composition in On-The-Fly
Computing."
author:
- first_name: Frederik Simon
full_name: Bäumer, Frederik Simon
id: '38837'
last_name: Bäumer
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
citation:
ama: 'Bäumer FS, Geierhos M. How to Deal with Inaccurate Service Descriptions in
On-The-Fly Computing: Open Challenges. In: Silberztein M, Atigui F, Kornyshova
E, Métais E, Meziane F, eds. Proceedings of the 23rd International Conference
on Natural Language and Information Systems. Vol 10859. Lecture Notes in Computer
Science. Cham, Switzerland: Springer; 2018:509-513. doi:10.1007/978-3-319-91947-8_53'
apa: 'Bäumer, F. S., & Geierhos, M. (2018). How to Deal with Inaccurate Service
Descriptions in On-The-Fly Computing: Open Challenges. In M. Silberztein, F. Atigui,
E. Kornyshova, E. Métais, & F. Meziane (Eds.), Proceedings of the 23rd
International Conference on Natural Language and Information Systems (Vol.
10859, pp. 509–513). Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-319-91947-8_53'
bibtex: '@inbook{Bäumer_Geierhos_2018, place={Cham, Switzerland}, series={Lecture
Notes in Computer Science}, title={How to Deal with Inaccurate Service Descriptions
in On-The-Fly Computing: Open Challenges}, volume={10859}, DOI={10.1007/978-3-319-91947-8_53},
booktitle={Proceedings of the 23rd International Conference on Natural Language
and Information Systems}, publisher={Springer}, author={Bäumer, Frederik Simon
and Geierhos, Michaela}, editor={Silberztein, Max and Atigui, Faten and Kornyshova,
Elena and Métais, Elisabeth and Meziane, Farid Editors}, year={2018}, pages={509–513},
collection={Lecture Notes in Computer Science} }'
chicago: 'Bäumer, Frederik Simon, and Michaela Geierhos. “How to Deal with Inaccurate
Service Descriptions in On-The-Fly Computing: Open Challenges.” In Proceedings
of the 23rd International Conference on Natural Language and Information Systems,
edited by Max Silberztein, Faten Atigui, Elena Kornyshova, Elisabeth Métais,
and Farid Meziane, 10859:509–13. Lecture Notes in Computer Science. Cham, Switzerland:
Springer, 2018. https://doi.org/10.1007/978-3-319-91947-8_53.'
ieee: 'F. S. Bäumer and M. Geierhos, “How to Deal with Inaccurate Service Descriptions
in On-The-Fly Computing: Open Challenges,” in Proceedings of the 23rd International
Conference on Natural Language and Information Systems, vol. 10859, M. Silberztein,
F. Atigui, E. Kornyshova, E. Métais, and F. Meziane, Eds. Cham, Switzerland: Springer,
2018, pp. 509–513.'
mla: 'Bäumer, Frederik Simon, and Michaela Geierhos. “How to Deal with Inaccurate
Service Descriptions in On-The-Fly Computing: Open Challenges.” Proceedings
of the 23rd International Conference on Natural Language and Information Systems,
edited by Max Silberztein et al., vol. 10859, Springer, 2018, pp. 509–13, doi:10.1007/978-3-319-91947-8_53.'
short: 'F.S. Bäumer, M. Geierhos, in: M. Silberztein, F. Atigui, E. Kornyshova,
E. Métais, F. Meziane (Eds.), Proceedings of the 23rd International Conference
on Natural Language and Information Systems, Springer, Cham, Switzerland, 2018,
pp. 509–513.'
conference:
end_date: 2018-06-18
location: Paris, France
name: 23rd International Conference on Natural Language and Information Systems
start_date: 2018-06-13
date_created: 2018-04-13T08:54:56Z
date_updated: 2022-01-06T06:55:47Z
ddc:
- '000'
department:
- _id: '36'
- _id: '1'
- _id: '579'
doi: 10.1007/978-3-319-91947-8_53
editor:
- first_name: 'Max '
full_name: 'Silberztein, Max '
last_name: Silberztein
- first_name: 'Faten '
full_name: 'Atigui, Faten '
last_name: Atigui
- first_name: 'Elena '
full_name: 'Kornyshova, Elena '
last_name: Kornyshova
- 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: ups
date_created: 2018-11-02T16:12:26Z
date_updated: 2018-11-02T16:12:26Z
file_id: '5326'
file_name: Bäumer-Geierhos2018_Chapter_HowToDealWithInaccurateService.pdf
file_size: 327508
relation: main_file
success: 1
file_date_updated: 2018-11-02T16:12:26Z
has_accepted_license: '1'
intvolume: ' 10859'
keyword:
- Requirements Extraction
- Temporal Reordering of Software Functions
- Inaccuracy Compensation
language:
- iso: eng
page: 509-513
place: Cham, Switzerland
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 23rd International Conference on Natural Language
and Information Systems
publication_identifier:
isbn:
- 978-3-319-91946-1
publication_status: published
publisher: Springer
quality_controlled: '1'
series_title: Lecture Notes in Computer Science
status: public
title: 'How to Deal with Inaccurate Service Descriptions in On-The-Fly Computing:
Open Challenges'
type: book_chapter
user_id: '477'
volume: 10859
year: '2018'
...