---
_id: '57240'
abstract:
- lang: eng
text: Validating assertions before adding them to a knowledge graph is an essential
part of its creation and maintenance. Due to the sheer size of knowledge graphs,
automatic fact-checking approaches have been developed. These approaches rely
on reference knowledge to decide whether a given assertion is correct. Recent
hybrid approaches achieve good results by including several knowledge sources.
However, it is often impractical to provide a sheer quantity of textual knowledge
or generate embedding models to leverage these hybrid approaches. We present FaVEL,
an approach that uses algorithm selection and ensemble learning to amalgamate
several existing fact-checking approaches that rely solely on a reference knowledge
graph and, hence, use fewer resources than current hybrid approaches. For our
evaluation, we create updated versions of two existing datasets and a new dataset
dubbed FaVEL-DS. Our evaluation compares our approach to 15 fact-checking approaches—including
the state-of-the-art approach HybridFC—on 3 datasets. Our results demonstrate
that FaVEL outperforms all other approaches significantly by at least 0.04 in
terms of the area under the ROC curve. Our source code, datasets, and evaluation
results are open-source and can be found at https://github.com/dice-group/favel.
author:
- first_name: Umair
full_name: Qudus, Umair
id: '83392'
last_name: Qudus
orcid: 0000-0001-6714-8729
- first_name: Michael
full_name: Röder, Michael
id: '67199'
last_name: Röder
orcid: https://orcid.org/0000-0002-8609-8277
- first_name: Franck Lionel
full_name: Tatkeu Pekarou, Franck Lionel
last_name: Tatkeu Pekarou
- first_name: Ana Alexandra
full_name: Morim da Silva, Ana Alexandra
id: '72108'
last_name: Morim da Silva
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Qudus U, Röder M, Tatkeu Pekarou FL, Morim da Silva AA, Ngonga Ngomo A-C.
FaVEL: Fact Validation Ensemble Learning. In: Rospocher M, Mehwish Alam, eds.
EKAW 2024. ; 2024.'
apa: 'Qudus, U., Röder, M., Tatkeu Pekarou, F. L., Morim da Silva, A. A., &
Ngonga Ngomo, A.-C. (2024). FaVEL: Fact Validation Ensemble Learning. In M. Rospocher
& Mehwish Alam (Eds.), EKAW 2024.'
bibtex: '@inproceedings{Qudus_Röder_Tatkeu Pekarou_Morim da Silva_Ngonga Ngomo_2024,
title={FaVEL: Fact Validation Ensemble Learning}, booktitle={EKAW 2024}, author={Qudus,
Umair and Röder, Michael and Tatkeu Pekarou, Franck Lionel and Morim da Silva,
Ana Alexandra and Ngonga Ngomo, Axel-Cyrille}, editor={Rospocher, Marco and Mehwish
Alam}, year={2024} }'
chicago: 'Qudus, Umair, Michael Röder, Franck Lionel Tatkeu Pekarou, Ana Alexandra
Morim da Silva, and Axel-Cyrille Ngonga Ngomo. “FaVEL: Fact Validation Ensemble
Learning.” In EKAW 2024, edited by Marco Rospocher and Mehwish Alam, 2024.'
ieee: 'U. Qudus, M. Röder, F. L. Tatkeu Pekarou, A. A. Morim da Silva, and A.-C.
Ngonga Ngomo, “FaVEL: Fact Validation Ensemble Learning,” in EKAW 2024,
Amsterdam, Netherlands, 2024.'
mla: 'Qudus, Umair, et al. “FaVEL: Fact Validation Ensemble Learning.” EKAW 2024,
edited by Marco Rospocher and Mehwish Alam, 2024.'
short: 'U. Qudus, M. Röder, F.L. Tatkeu Pekarou, A.A. Morim da Silva, A.-C. Ngonga
Ngomo, in: M. Rospocher, Mehwish Alam (Eds.), EKAW 2024, 2024.'
conference:
end_date: 2024-11-28
location: Amsterdam, Netherlands
name: 24th International Conference on Knowledge Engineering and Knowledge Management
start_date: 2024-11-26
corporate_editor:
- Mehwish Alam
date_created: 2024-11-19T14:12:49Z
date_updated: 2025-09-11T09:48:12Z
ddc:
- '600'
department:
- _id: '34'
editor:
- first_name: Marco
full_name: Rospocher, Marco
last_name: Rospocher
file:
- access_level: closed
content_type: application/pdf
creator: uqudus
date_created: 2024-11-19T14:14:14Z
date_updated: 2024-11-19T14:14:14Z
file_id: '57241'
file_name: favel.pdf
file_size: 190661
relation: main_file
success: 1
file_date_updated: 2024-11-19T14:14:14Z
has_accepted_license: '1'
keyword:
- fact checking
- ensemble learning
- transfer learning
- knowledge management.
language:
- iso: eng
popular_science: '1'
project:
- _id: '412'
name: 'NEBULA: Nutzerzentrierte KI-basierte Erkennung von Fake-News und Fehlinformationen'
- _id: '285'
name: 'SAIL: SAIL - Nachhaltiger Lebenszyklus von intelligenten soziotechnischen
Systemen'
- _id: '410'
name: 'KnowGraphs: KnowGraphs: Knowledge Graphs at Scale'
publication: EKAW 2024
quality_controlled: '1'
status: public
title: 'FaVEL: Fact Validation Ensemble Learning'
type: conference
user_id: '83392'
year: '2024'
...
---
_id: '45270'
abstract:
- lang: eng
text: Clinical depression is a serious mental disorder that poses challenges for
both personal and public health. Millions of people struggle with depression each
year, but for many, the disorder goes undiagnosed or untreated. Over the last
decade, early depression detection on social media emerged as an interdisciplinary
research field. However, there is still a gap in detecting hesitant, depression-susceptible
individuals with minimal direct depressive signals at an early stage. We, therefore,
take up this open point and leverage posts from Reddit to fill the addressed gap.
Our results demonstrate the potential of contemporary Transformer architectures
in yielding promising predictive capabilities for mental health research. Furthermore,
we investigate the model’s interpretability using a surrogate and a topic modeling
approach. Based on our findings, we consider this work as a further step towards
developing a better understanding of mental eHealth and hope that our results
can support the development of future technologies.
author:
- first_name: Haya
full_name: Halimeh, Haya
id: '87673'
last_name: Halimeh
- first_name: Matthew
full_name: Caron, Matthew
id: '60721'
last_name: Caron
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: 'Halimeh H, Caron M, Müller O. Early Depression Detection with Transformer
Models: Analyzing the Relationship between Linguistic and Psychology-Based Features.
In: Hawaii International Conference on System Sciences. ; 2023.'
apa: 'Halimeh, H., Caron, M., & Müller, O. (2023). Early Depression Detection
with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based
Features. Hawaii International Conference on System Sciences. Hawaii International
Conference on System Sciences.'
bibtex: '@inproceedings{Halimeh_Caron_Müller_2023, title={Early Depression Detection
with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based
Features}, booktitle={Hawaii International Conference on System Sciences}, author={Halimeh,
Haya and Caron, Matthew and Müller, Oliver}, year={2023} }'
chicago: 'Halimeh, Haya, Matthew Caron, and Oliver Müller. “Early Depression Detection
with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based
Features.” In Hawaii International Conference on System Sciences, 2023.'
ieee: 'H. Halimeh, M. Caron, and O. Müller, “Early Depression Detection with Transformer
Models: Analyzing the Relationship between Linguistic and Psychology-Based Features,”
presented at the Hawaii International Conference on System Sciences, 2023.'
mla: 'Halimeh, Haya, et al. “Early Depression Detection with Transformer Models:
Analyzing the Relationship between Linguistic and Psychology-Based Features.”
Hawaii International Conference on System Sciences, 2023.'
short: 'H. Halimeh, M. Caron, O. Müller, in: Hawaii International Conference on
System Sciences, 2023.'
conference:
end_date: 2023-01-06
name: Hawaii International Conference on System Sciences
start_date: 2023-01-03
date_created: 2023-05-25T10:25:21Z
date_updated: 2024-01-10T15:16:37Z
department:
- _id: '195'
- _id: '196'
keyword:
- Social Media and Healthcare Technology
- early depression detection
- liwc
- mental health
- transfer learning
- transformer architectures
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://scholarspace.manoa.hawaii.edu/items/2ddab486-5d2f-4302-8de3-a8b24017da3d
oa: '1'
publication: Hawaii International Conference on System Sciences
publication_status: published
related_material:
link:
- relation: confirmation
url: https://hdl.handle.net/10125/103046
status: public
title: 'Early Depression Detection with Transformer Models: Analyzing the Relationship
between Linguistic and Psychology-Based Features'
type: conference
user_id: '60721'
year: '2023'
...
---
_id: '50479'
abstract:
- lang: eng
text: Verifying assertions is an essential part of creating and maintaining knowledge
graphs. Most often, this task cannot be carried out manually due to the sheer
size of modern knowledge graphs. Hence, automatic fact-checking approaches have
been proposed over the last decade. These approaches aim to compute automatically
whether a given assertion is correct or incorrect. However, most fact-checking
approaches are binary classifiers that fail to consider the volatility of some
assertions, i.e., the fact that such assertions are only valid at certain times
or for specific time intervals. Moreover, the few approaches able to predict when
an assertion was valid (i.e., time-point prediction approaches) rely on manual
feature engineering. This paper presents TEMPORALFC, a temporal fact-checking
approach that uses multiple sources of background knowledge to assess the veracity
and temporal validity of a given assertion. We evaluate TEMPORALFC on two datasets
and compare it to the state of the art in fact-checking and time-point prediction.
Our results suggest that TEMPORALFC outperforms the state of the art on the fact-checking
task by 0.13 to 0.15 in terms of Area Under the Receiver Operating Characteristic
curve and on the time-point prediction task by 0.25 to 0.27 in terms of Mean Reciprocal
Rank. Our code is open-source and can be found at https://github.com/dice-group/TemporalFC.
author:
- first_name: Umair
full_name: Qudus, Umair
last_name: Qudus
- first_name: Michael
full_name: Röder, Michael
last_name: Röder
- first_name: Sabrina
full_name: Kirrane, Sabrina
last_name: Kirrane
- first_name: Axel-Cyrille Ngonga
full_name: Ngomo, Axel-Cyrille Ngonga
last_name: Ngomo
citation:
ama: 'Qudus U, Röder M, Kirrane S, Ngomo A-CN. TemporalFC: A Temporal Fact Checking
Approach over Knowledge Graphs. In: R. Payne T, Presutti V, Qi G, et al., eds.
The Semantic Web – ISWC 2023. Vol 14265. Lecture Notes in Computer Science.
Springer, Cham; 2023:465–483. doi:10.1007/978-3-031-47240-4_25'
apa: 'Qudus, U., Röder, M., Kirrane, S., & Ngomo, A.-C. N. (2023). TemporalFC:
A Temporal Fact Checking Approach over Knowledge Graphs. In T. R. Payne, V. Presutti,
G. Qi, M. Poveda-Villalón, G. Stoilos, L. Hollink, Z. Kaoudi, G. Cheng, &
J. Li (Eds.), The Semantic Web – ISWC 2023 (Vol. 14265, pp. 465–483). Springer,
Cham. https://doi.org/10.1007/978-3-031-47240-4_25'
bibtex: '@inproceedings{Qudus_Röder_Kirrane_Ngomo_2023, place={Cham}, series={ Lecture
Notes in Computer Science}, title={TemporalFC: A Temporal Fact Checking Approach
over Knowledge Graphs}, volume={14265}, DOI={10.1007/978-3-031-47240-4_25},
booktitle={The Semantic Web – ISWC 2023}, publisher={Springer, Cham}, author={Qudus,
Umair and Röder, Michael and Kirrane, Sabrina and Ngomo, Axel-Cyrille Ngonga},
editor={R. Payne, Terry and Presutti, Valentina and Qi, Guilin and Poveda-Villalón,
María and Stoilos, Giorgos and Hollink, Laura and Kaoudi, Zoi and Cheng, Gong
and Li, Juanzi}, year={2023}, pages={465–483}, collection={ Lecture Notes in Computer
Science} }'
chicago: 'Qudus, Umair, Michael Röder, Sabrina Kirrane, and Axel-Cyrille Ngonga
Ngomo. “TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs.”
In The Semantic Web – ISWC 2023, edited by Terry R. Payne, Valentina Presutti,
Guilin Qi, María Poveda-Villalón, Giorgos Stoilos, Laura Hollink, Zoi Kaoudi,
Gong Cheng, and Juanzi Li, 14265:465–483. Lecture Notes in Computer Science.
Cham: Springer, Cham, 2023. https://doi.org/10.1007/978-3-031-47240-4_25.'
ieee: 'U. Qudus, M. Röder, S. Kirrane, and A.-C. N. Ngomo, “TemporalFC: A Temporal
Fact Checking Approach over Knowledge Graphs,” in The Semantic Web – ISWC 2023,
Athens, Greece, 2023, vol. 14265, pp. 465–483, doi: 10.1007/978-3-031-47240-4_25.'
mla: 'Qudus, Umair, et al. “TemporalFC: A Temporal Fact Checking Approach over Knowledge
Graphs.” The Semantic Web – ISWC 2023, edited by Terry R. Payne et al.,
vol. 14265, Springer, Cham, 2023, pp. 465–483, doi:10.1007/978-3-031-47240-4_25.'
short: 'U. Qudus, M. Röder, S. Kirrane, A.-C.N. Ngomo, in: T. R. Payne, V. Presutti,
G. Qi, M. Poveda-Villalón, G. Stoilos, L. Hollink, Z. Kaoudi, G. Cheng, J. Li
(Eds.), The Semantic Web – ISWC 2023, Springer, Cham, Cham, 2023, pp. 465–483.'
conference:
end_date: 2023-11-10
location: Athens, Greece
name: The Semantic Web – ISWC 2023
start_date: 2023-11-06
date_created: 2024-01-13T11:22:15Z
date_updated: 2024-01-13T11:48:28Z
ddc:
- '006'
department:
- _id: '34'
doi: 10.1007/978-3-031-47240-4_25
editor:
- first_name: Terry
full_name: R. Payne, Terry
last_name: R. Payne
- first_name: Valentina
full_name: Presutti, Valentina
last_name: Presutti
- first_name: Guilin
full_name: Qi, Guilin
last_name: Qi
- first_name: María
full_name: Poveda-Villalón, María
last_name: Poveda-Villalón
- first_name: Giorgos
full_name: Stoilos, Giorgos
last_name: Stoilos
- first_name: Laura
full_name: Hollink, Laura
last_name: Hollink
- first_name: Zoi
full_name: Kaoudi, Zoi
last_name: Kaoudi
- first_name: Gong
full_name: Cheng, Gong
last_name: Cheng
- first_name: Juanzi
full_name: Li, Juanzi
last_name: Li
file:
- access_level: closed
content_type: application/pdf
creator: uqudus
date_created: 2024-01-13T11:25:48Z
date_updated: 2024-01-13T11:25:48Z
file_id: '50480'
file_name: ISWC 2023 TemporalFC-A Temporal Fact Checking approach over Knowledge
Graphs.pdf
file_size: 1944818
relation: main_file
success: 1
file_date_updated: 2024-01-13T11:25:48Z
has_accepted_license: '1'
intvolume: ' 14265'
jel:
- C
keyword:
- temporal fact checking · ensemble learning · transfer learning · time-point prediction
· temporal knowledge graphs
language:
- iso: eng
page: 465–483
place: Cham
project:
- _id: '410'
grant_number: '860801'
name: 'KnowGraphs: KnowGraphs: Knowledge Graphs at Scale'
publication: The Semantic Web – ISWC 2023
publication_identifier:
isbn:
- '9783031472398'
- '9783031472404'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer, Cham
series_title: ' Lecture Notes in Computer Science'
status: public
title: 'TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs'
type: conference
user_id: '83392'
volume: 14265
year: '2023'
...
---
_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: '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'
...