---
_id: '43395'
author:
- first_name: Roman
full_name: Trentinaglia, Roman
id: '49934'
last_name: Trentinaglia
orcid: 0000-0001-9728-4991
- first_name: Sven
full_name: Merschjohann, Sven
id: '11394'
last_name: Merschjohann
- first_name: Markus
full_name: Fockel, Markus
id: '8472'
last_name: Fockel
orcid: 0000-0002-1269-0702
- first_name: Hendrik
full_name: Eikerling, Hendrik
id: '29279'
last_name: Eikerling
citation:
ama: 'Trentinaglia R, Merschjohann S, Fockel M, Eikerling H. Eliciting Security
Requirements – An Experience Report. In: REFSQ 2023: Requirements Engineering:
Foundation for Software Quality. Springer Nature Switzerland; 2023. doi:10.1007/978-3-031-29786-1_25'
apa: 'Trentinaglia, R., Merschjohann, S., Fockel, M., & Eikerling, H. (2023).
Eliciting Security Requirements – An Experience Report. REFSQ 2023: Requirements
Engineering: Foundation for Software Quality. https://doi.org/10.1007/978-3-031-29786-1_25'
bibtex: '@inproceedings{Trentinaglia_Merschjohann_Fockel_Eikerling_2023, place={Cham},
title={Eliciting Security Requirements – An Experience Report}, DOI={10.1007/978-3-031-29786-1_25},
booktitle={REFSQ 2023: Requirements Engineering: Foundation for Software Quality},
publisher={Springer Nature Switzerland}, author={Trentinaglia, Roman and Merschjohann,
Sven and Fockel, Markus and Eikerling, Hendrik}, year={2023} }'
chicago: 'Trentinaglia, Roman, Sven Merschjohann, Markus Fockel, and Hendrik Eikerling.
“Eliciting Security Requirements – An Experience Report.” In REFSQ 2023: Requirements
Engineering: Foundation for Software Quality. Cham: Springer Nature Switzerland,
2023. https://doi.org/10.1007/978-3-031-29786-1_25.'
ieee: 'R. Trentinaglia, S. Merschjohann, M. Fockel, and H. Eikerling, “Eliciting
Security Requirements – An Experience Report,” 2023, doi: 10.1007/978-3-031-29786-1_25.'
mla: 'Trentinaglia, Roman, et al. “Eliciting Security Requirements – An Experience
Report.” REFSQ 2023: Requirements Engineering: Foundation for Software Quality,
Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-29786-1_25.'
short: 'R. Trentinaglia, S. Merschjohann, M. Fockel, H. Eikerling, in: REFSQ 2023:
Requirements Engineering: Foundation for Software Quality, Springer Nature Switzerland,
Cham, 2023.'
date_created: 2023-04-04T12:47:31Z
date_updated: 2023-04-04T12:51:41Z
department:
- _id: '241'
- _id: '662'
doi: 10.1007/978-3-031-29786-1_25
language:
- iso: eng
place: Cham
publication: 'REFSQ 2023: Requirements Engineering: Foundation for Software Quality'
publication_identifier:
isbn:
- '9783031297854'
- '9783031297861'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: Eliciting Security Requirements – An Experience Report
type: conference
user_id: '8472'
year: '2023'
...
---
_id: '44769'
author:
- first_name: Jannik
full_name: Castenow, Jannik
id: '38705'
last_name: Castenow
- first_name: Jonas
full_name: Harbig, Jonas
id: '47213'
last_name: Harbig
- first_name: Friedhelm
full_name: Meyer auf der Heide, Friedhelm
id: '15523'
last_name: Meyer auf der Heide
citation:
ama: 'Castenow J, Harbig J, Meyer auf der Heide F. Unifying Gathering Protocols
for Swarms of Mobile Robots. In: Lecture Notes in Computer Science. Springer
International Publishing; 2023. doi:10.1007/978-3-031-30448-4_1'
apa: Castenow, J., Harbig, J., & Meyer auf der Heide, F. (2023). Unifying Gathering
Protocols for Swarms of Mobile Robots. In Lecture Notes in Computer Science.
Springer International Publishing. https://doi.org/10.1007/978-3-031-30448-4_1
bibtex: '@inbook{Castenow_Harbig_Meyer auf der Heide_2023, place={Cham}, title={Unifying
Gathering Protocols for Swarms of Mobile Robots}, DOI={10.1007/978-3-031-30448-4_1},
booktitle={Lecture Notes in Computer Science}, publisher={Springer International
Publishing}, author={Castenow, Jannik and Harbig, Jonas and Meyer auf der Heide,
Friedhelm}, year={2023} }'
chicago: 'Castenow, Jannik, Jonas Harbig, and Friedhelm Meyer auf der Heide. “Unifying
Gathering Protocols for Swarms of Mobile Robots.” In Lecture Notes in Computer
Science. Cham: Springer International Publishing, 2023. https://doi.org/10.1007/978-3-031-30448-4_1.'
ieee: 'J. Castenow, J. Harbig, and F. Meyer auf der Heide, “Unifying Gathering Protocols
for Swarms of Mobile Robots,” in Lecture Notes in Computer Science, Cham:
Springer International Publishing, 2023.'
mla: Castenow, Jannik, et al. “Unifying Gathering Protocols for Swarms of Mobile
Robots.” Lecture Notes in Computer Science, Springer International Publishing,
2023, doi:10.1007/978-3-031-30448-4_1.
short: 'J. Castenow, J. Harbig, F. Meyer auf der Heide, in: Lecture Notes in Computer
Science, Springer International Publishing, Cham, 2023.'
date_created: 2023-05-11T13:13:45Z
date_updated: 2023-05-11T13:14:43Z
department:
- _id: '63'
doi: 10.1007/978-3-031-30448-4_1
language:
- iso: eng
place: Cham
project:
- _id: '106'
name: 'Algorithmen für Schwarmrobotik: Verteiltes Rechnen trifft Dynamische Systeme'
publication: Lecture Notes in Computer Science
publication_identifier:
isbn:
- '9783031304477'
- '9783031304484'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer International Publishing
status: public
title: Unifying Gathering Protocols for Swarms of Mobile Robots
type: book_chapter
user_id: '38705'
year: '2023'
...
---
_id: '46516'
abstract:
- lang: eng
text: Linked knowledge graphs build the backbone of many data-driven applications
such as search engines, conversational agents and e-commerce solutions. Declarative
link discovery frameworks use complex link specifications to express the conditions
under which a link between two resources can be deemed to exist. However, understanding
such complex link specifications is a challenging task for non-expert users of
link discovery frameworks. In this paper, we address this drawback by devising
NMV-LS, a language model-based verbalization approach for translating complex
link specifications into natural language. NMV-LS relies on the results of rule-based
link specification verbalization to apply continuous training on T5, a large language
model based on the Transformerarchitecture. We evaluated NMV-LS on English and
German datasets using well-known machine translation metrics such as BLUE, METEOR,
ChrF++ and TER. Our results suggest that our approach achieves a verbalization
performance close to that of humans and outperforms state of the art approaches.
Our source code and datasets are publicly available at https://github.com/dice-group/NMV-LS.
author:
- first_name: Abdullah Fathi Ahmed
full_name: Ahmed, Abdullah Fathi Ahmed
id: '29670'
last_name: Ahmed
- first_name: Asep Fajar
full_name: Firmansyah, Asep Fajar
id: '76787'
last_name: Firmansyah
- first_name: Mohamed
full_name: Sherif, Mohamed
id: '67234'
last_name: Sherif
orcid: https://orcid.org/0000-0002-9927-2203
- first_name: Diego
full_name: Moussallem, Diego
id: '71635'
last_name: Moussallem
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Ahmed AFA, Firmansyah AF, Sherif M, Moussallem D, Ngonga Ngomo A-C. Explainable
Integration of Knowledge Graphs Using Large Language Models. In: Natural Language
Processing and Information Systems. Springer Nature Switzerland; 2023. doi:10.1007/978-3-031-35320-8_9'
apa: Ahmed, A. F. A., Firmansyah, A. F., Sherif, M., Moussallem, D., & Ngonga
Ngomo, A.-C. (2023). Explainable Integration of Knowledge Graphs Using Large Language
Models. In Natural Language Processing and Information Systems. Springer
Nature Switzerland. https://doi.org/10.1007/978-3-031-35320-8_9
bibtex: '@inbook{Ahmed_Firmansyah_Sherif_Moussallem_Ngonga Ngomo_2023, place={Cham},
title={Explainable Integration of Knowledge Graphs Using Large Language Models},
DOI={10.1007/978-3-031-35320-8_9},
booktitle={Natural Language Processing and Information Systems}, publisher={Springer
Nature Switzerland}, author={Ahmed, Abdullah Fathi Ahmed and Firmansyah, Asep
Fajar and Sherif, Mohamed and Moussallem, Diego and Ngonga Ngomo, Axel-Cyrille},
year={2023} }'
chicago: 'Ahmed, Abdullah Fathi Ahmed, Asep Fajar Firmansyah, Mohamed Sherif, Diego
Moussallem, and Axel-Cyrille Ngonga Ngomo. “Explainable Integration of Knowledge
Graphs Using Large Language Models.” In Natural Language Processing and Information
Systems. Cham: Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-35320-8_9.'
ieee: 'A. F. A. Ahmed, A. F. Firmansyah, M. Sherif, D. Moussallem, and A.-C. Ngonga
Ngomo, “Explainable Integration of Knowledge Graphs Using Large Language Models,”
in Natural Language Processing and Information Systems, Cham: Springer
Nature Switzerland, 2023.'
mla: Ahmed, Abdullah Fathi Ahmed, et al. “Explainable Integration of Knowledge Graphs
Using Large Language Models.” Natural Language Processing and Information Systems,
Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-35320-8_9.
short: 'A.F.A. Ahmed, A.F. Firmansyah, M. Sherif, D. Moussallem, A.-C. Ngonga Ngomo,
in: Natural Language Processing and Information Systems, Springer Nature Switzerland,
Cham, 2023.'
date_created: 2023-08-16T08:57:11Z
date_updated: 2023-08-16T09:15:42Z
department:
- _id: '34'
doi: 10.1007/978-3-031-35320-8_9
language:
- iso: eng
place: Cham
publication: Natural Language Processing and Information Systems
publication_identifier:
isbn:
- '9783031353192'
- '9783031353208'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: Explainable Integration of Knowledge Graphs Using Large Language Models
type: book_chapter
user_id: '67234'
year: '2023'
...
---
_id: '46572'
abstract:
- lang: eng
text: Indonesian is classified as underrepresented in the Natural Language Processing
(NLP) field, despite being the tenth most spoken language in the world with 198
million speakers. The paucity of datasets is recognized as the main reason for
the slow advancements in NLP research for underrepresented languages. Significant
attempts were made in 2020 to address this drawback for Indonesian. The Indonesian
Natural Language Understanding (IndoNLU) benchmark was introduced alongside IndoBERT
pre-trained language model. The second benchmark, Indonesian Language Evaluation
Montage (IndoLEM), was presented in the same year. These benchmarks support several
tasks, including Named Entity Recognition (NER). However, all NER datasets are
in the public domain and do not contain domain-specific datasets. To alleviate
this drawback, we introduce IndQNER, a manually annotated NER benchmark dataset
in the religious domain that adheres to a meticulously designed annotation guideline.
Since Indonesia has the world’s largest Muslim population, we build the dataset
from the Indonesian translation of the Quran. The dataset includes 2475 named
entities representing 18 different classes. To assess the annotation quality of
IndQNER, we perform experiments with BiLSTM and CRF-based NER, as well as IndoBERT
fine-tuning. The results reveal that the first model outperforms the second model
achieving 0.98 F1 points. This outcome indicates that IndQNER may be an acceptable
evaluation metric for Indonesian NER tasks in the aforementioned domain, widening
the research’s domain range.
author:
- first_name: Ria Hari
full_name: Gusmita, Ria Hari
last_name: Gusmita
- first_name: Asep Fajar
full_name: Firmansyah, Asep Fajar
last_name: Firmansyah
- first_name: Diego
full_name: Moussallem, Diego
last_name: Moussallem
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
last_name: Ngonga Ngomo
citation:
ama: 'Gusmita RH, Firmansyah AF, Moussallem D, Ngonga Ngomo A-C. IndQNER: Named
Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran.
In: Natural Language Processing and Information Systems. Springer Nature
Switzerland; 2023. doi:10.1007/978-3-031-35320-8_12'
apa: 'Gusmita, R. H., Firmansyah, A. F., Moussallem, D., & Ngonga Ngomo, A.-C.
(2023). IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian
Translation of the Quran. In Natural Language Processing and Information Systems.
International Conference on Applications of Natural Language to Information Systems
(NLDB) 2023, Derby, UK. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-35320-8_12'
bibtex: '@inbook{Gusmita_Firmansyah_Moussallem_Ngonga Ngomo_2023, place={Cham},
title={IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian
Translation of the Quran}, DOI={10.1007/978-3-031-35320-8_12},
booktitle={Natural Language Processing and Information Systems}, publisher={Springer
Nature Switzerland}, author={Gusmita, Ria Hari and Firmansyah, Asep Fajar and
Moussallem, Diego and Ngonga Ngomo, Axel-Cyrille}, year={2023} }'
chicago: 'Gusmita, Ria Hari, Asep Fajar Firmansyah, Diego Moussallem, and Axel-Cyrille
Ngonga Ngomo. “IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian
Translation of the Quran.” In Natural Language Processing and Information Systems.
Cham: Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-35320-8_12.'
ieee: 'R. H. Gusmita, A. F. Firmansyah, D. Moussallem, and A.-C. Ngonga Ngomo, “IndQNER:
Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran,”
in Natural Language Processing and Information Systems, Cham: Springer
Nature Switzerland, 2023.'
mla: 'Gusmita, Ria Hari, et al. “IndQNER: Named Entity Recognition Benchmark Dataset
from the Indonesian Translation of the Quran.” Natural Language Processing
and Information Systems, Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-35320-8_12.'
short: 'R.H. Gusmita, A.F. Firmansyah, D. Moussallem, A.-C. Ngonga Ngomo, in: Natural
Language Processing and Information Systems, Springer Nature Switzerland, Cham,
2023.'
conference:
end_date: 2023-06-23
location: Derby, UK
name: International Conference on Applications of Natural Language to Information
Systems (NLDB) 2023
start_date: 2023-06-21
date_created: 2023-08-17T12:41:45Z
date_updated: 2023-08-17T12:52:03Z
department:
- _id: '574'
doi: 10.1007/978-3-031-35320-8_12
language:
- iso: eng
place: Cham
publication: Natural Language Processing and Information Systems
publication_identifier:
isbn:
- '9783031353192'
- '9783031353208'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: 'IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation
of the Quran'
type: book_chapter
user_id: '76787'
year: '2023'
...
---
_id: '46867'
author:
- first_name: Peter
full_name: Dieter, Peter
id: '88592'
last_name: Dieter
citation:
ama: 'Dieter P. A Regret Policy for the Dynamic Vehicle Routing Problem with Time
Windows. In: Lecture Notes in Computer Science. Springer Nature Switzerland;
2023. doi:10.1007/978-3-031-43612-3_14'
apa: Dieter, P. (2023). A Regret Policy for the Dynamic Vehicle Routing Problem
with Time Windows. In Lecture Notes in Computer Science. Springer Nature
Switzerland. https://doi.org/10.1007/978-3-031-43612-3_14
bibtex: '@inbook{Dieter_2023, place={Cham}, title={A Regret Policy for the Dynamic
Vehicle Routing Problem with Time Windows}, DOI={10.1007/978-3-031-43612-3_14},
booktitle={Lecture Notes in Computer Science}, publisher={Springer Nature Switzerland},
author={Dieter, Peter}, year={2023} }'
chicago: 'Dieter, Peter. “A Regret Policy for the Dynamic Vehicle Routing Problem
with Time Windows.” In Lecture Notes in Computer Science. Cham: Springer
Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-43612-3_14.'
ieee: 'P. Dieter, “A Regret Policy for the Dynamic Vehicle Routing Problem with Time
Windows,” in Lecture Notes in Computer Science, Cham: Springer Nature Switzerland,
2023.'
mla: Dieter, Peter. “A Regret Policy for the Dynamic Vehicle Routing Problem with Time
Windows.” Lecture Notes in Computer Science, Springer Nature Switzerland,
2023, doi:10.1007/978-3-031-43612-3_14.
short: 'P. Dieter, in: Lecture Notes in Computer Science, Springer Nature Switzerland,
Cham, 2023.'
date_created: 2023-09-07T17:46:08Z
date_updated: 2023-09-07T17:52:46Z
ddc:
- '000'
department:
- _id: '277'
doi: 10.1007/978-3-031-43612-3_14
has_accepted_license: '1'
language:
- iso: eng
place: Cham
publication: Lecture Notes in Computer Science
publication_identifier:
isbn:
- '9783031436116'
- '9783031436123'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: A Regret Policy for the Dynamic Vehicle Routing Problem with Time Windows
type: book_chapter
user_id: '51811'
year: '2023'
...
---
_id: '47421'
abstract:
- lang: eng
text: Class expression learning in description logics has long been regarded as
an iterative search problem in an infinite conceptual space. Each iteration of
the search process invokes a reasoner and a heuristic function. The reasoner finds
the instances of the current expression, and the heuristic function computes the
information gain and decides on the next step to be taken. As the size of the
background knowledge base grows, search-based approaches for class expression
learning become prohibitively slow. Current neural class expression synthesis
(NCES) approaches investigate the use of neural networks for class expression
learning in the attributive language with complement (ALC). While they show significant
improvements over search-based approaches in runtime and quality of the computed
solutions, they rely on the availability of pretrained embeddings for the input
knowledge base. Moreover, they are not applicable to ontologies in more expressive
description logics. In this paper, we propose a novel NCES approach which extends
the state of the art to the description logic ALCHIQ(D). Our extension, dubbed
NCES2, comes with an improved training data generator and does not require pretrained
embeddings for the input knowledge base as both the embedding model and the class
expression synthesizer are trained jointly. Empirical results on benchmark datasets
suggest that our approach inherits the scalability capability of current NCES
instances with the additional advantage that it supports more complex learning
problems. NCES2 achieves the highest performance overall when compared to search-based
approaches and to its predecessor NCES. We provide our source code, datasets,
and pretrained models at https://github.com/dice-group/NCES2.
author:
- first_name: N'Dah Jean
full_name: Kouagou, N'Dah Jean
id: '87189'
last_name: Kouagou
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Caglar
full_name: Demir, Caglar
id: '43817'
last_name: Demir
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Kouagou NJ, Heindorf S, Demir C, Ngonga Ngomo A-C. Neural Class Expression
Synthesis in ALCHIQ(D). In: Machine Learning and Knowledge Discovery in Databases:
Research Track. Springer Nature Switzerland; 2023. doi:10.1007/978-3-031-43421-1_12'
apa: 'Kouagou, N. J., Heindorf, S., Demir, C., & Ngonga Ngomo, A.-C. (2023).
Neural Class Expression Synthesis in ALCHIQ(D). In Machine Learning and Knowledge
Discovery in Databases: Research Track. European Conference on Machine Learning
and Principles and Practice of Knowledge Discovery in Databases, Turin. Springer
Nature Switzerland. https://doi.org/10.1007/978-3-031-43421-1_12'
bibtex: '@inbook{Kouagou_Heindorf_Demir_Ngonga Ngomo_2023, place={Cham}, title={Neural
Class Expression Synthesis in ALCHIQ(D)}, DOI={10.1007/978-3-031-43421-1_12},
booktitle={Machine Learning and Knowledge Discovery in Databases: Research Track},
publisher={Springer Nature Switzerland}, author={Kouagou, N’Dah Jean and Heindorf,
Stefan and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2023} }'
chicago: 'Kouagou, N’Dah Jean, Stefan Heindorf, Caglar Demir, and Axel-Cyrille Ngonga
Ngomo. “Neural Class Expression Synthesis in ALCHIQ(D).” In Machine Learning
and Knowledge Discovery in Databases: Research Track. Cham: Springer Nature
Switzerland, 2023. https://doi.org/10.1007/978-3-031-43421-1_12.'
ieee: 'N. J. Kouagou, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “Neural Class
Expression Synthesis in ALCHIQ(D),” in Machine Learning and Knowledge Discovery
in Databases: Research Track, Cham: Springer Nature Switzerland, 2023.'
mla: 'Kouagou, N’Dah Jean, et al. “Neural Class Expression Synthesis in ALCHIQ(D).”
Machine Learning and Knowledge Discovery in Databases: Research Track,
Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-43421-1_12.'
short: 'N.J. Kouagou, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: Machine Learning
and Knowledge Discovery in Databases: Research Track, Springer Nature Switzerland,
Cham, 2023.'
conference:
end_date: 2023-09-22
location: Turin
name: European Conference on Machine Learning and Principles and Practice of Knowledge
Discovery in Databases
start_date: 2023-09-18
date_created: 2023-09-25T13:42:01Z
date_updated: 2023-11-21T09:20:31Z
department:
- _id: '760'
- _id: '574'
doi: 10.1007/978-3-031-43421-1_12
language:
- iso: eng
place: Cham
publication: 'Machine Learning and Knowledge Discovery in Databases: Research Track'
publication_identifier:
isbn:
- '9783031434204'
- '9783031434211'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: Neural Class Expression Synthesis in ALCHIQ(D)
type: book_chapter
user_id: '11871'
year: '2023'
...
---
_id: '47953'
author:
- first_name: Jaroslaw
full_name: Kornowicz, Jaroslaw
id: '44029'
last_name: Kornowicz
- first_name: Kirsten
full_name: Thommes, Kirsten
id: '72497'
last_name: Thommes
citation:
ama: Kornowicz J, Thommes K. Aggregating Human Domain Knowledge for Feature Ranking.
Artificial Intelligence in HCI. Published online 2023. doi:10.1007/978-3-031-35891-3_7
apa: Kornowicz, J., & Thommes, K. (2023). Aggregating Human Domain Knowledge
for Feature Ranking. Artificial Intelligence in HCI. https://doi.org/10.1007/978-3-031-35891-3_7
bibtex: '@article{Kornowicz_Thommes_2023, title={Aggregating Human Domain Knowledge
for Feature Ranking}, DOI={10.1007/978-3-031-35891-3_7},
journal={Artificial Intelligence in HCI}, publisher={Springer Nature Switzerland},
author={Kornowicz, Jaroslaw and Thommes, Kirsten}, year={2023} }'
chicago: Kornowicz, Jaroslaw, and Kirsten Thommes. “Aggregating Human Domain Knowledge
for Feature Ranking.” Artificial Intelligence in HCI, 2023. https://doi.org/10.1007/978-3-031-35891-3_7.
ieee: 'J. Kornowicz and K. Thommes, “Aggregating Human Domain Knowledge for Feature
Ranking,” Artificial Intelligence in HCI, 2023, doi: 10.1007/978-3-031-35891-3_7.'
mla: Kornowicz, Jaroslaw, and Kirsten Thommes. “Aggregating Human Domain Knowledge
for Feature Ranking.” Artificial Intelligence in HCI, Springer Nature Switzerland,
2023, doi:10.1007/978-3-031-35891-3_7.
short: J. Kornowicz, K. Thommes, Artificial Intelligence in HCI (2023).
date_created: 2023-10-11T08:01:00Z
date_updated: 2023-12-05T10:15:37Z
department:
- _id: '184'
- _id: '178'
doi: 10.1007/978-3-031-35891-3_7
language:
- iso: eng
project:
- _id: '125'
name: 'TRR 318 - C2: TRR 318 - Subproject C2'
publication: Artificial Intelligence in HCI
publication_identifier:
isbn:
- '9783031358906'
- '9783031358913'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: Aggregating Human Domain Knowledge for Feature Ranking
type: journal_article
user_id: '42933'
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
license: https://creativecommons.org/publicdomain/zero/1.0/
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
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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: '46191'
author:
- first_name: Christoph
full_name: Alt, Christoph
id: '100625'
last_name: Alt
- first_name: Tobias
full_name: Kenter, Tobias
id: '3145'
last_name: Kenter
- first_name: Sara
full_name: Faghih-Naini, Sara
last_name: Faghih-Naini
- first_name: Jennifer
full_name: Faj, Jennifer
id: '78722'
last_name: Faj
- first_name: Jan-Oliver
full_name: Opdenhövel, Jan-Oliver
last_name: Opdenhövel
- first_name: Christian
full_name: Plessl, Christian
id: '16153'
last_name: Plessl
orcid: 0000-0001-5728-9982
- first_name: Vadym
full_name: Aizinger, Vadym
last_name: Aizinger
- first_name: Jan
full_name: Hönig, Jan
last_name: Hönig
- first_name: Harald
full_name: Köstler, Harald
last_name: Köstler
citation:
ama: 'Alt C, Kenter T, Faghih-Naini S, et al. Shallow Water DG Simulations on FPGAs:
Design and Comparison of a Novel Code Generation Pipeline. In: Lecture Notes
in Computer Science. Springer Nature Switzerland; 2023. doi:10.1007/978-3-031-32041-5_5'
apa: 'Alt, C., Kenter, T., Faghih-Naini, S., Faj, J., Opdenhövel, J.-O., Plessl,
C., Aizinger, V., Hönig, J., & Köstler, H. (2023). Shallow Water DG Simulations
on FPGAs: Design and Comparison of a Novel Code Generation Pipeline. In Lecture
Notes in Computer Science. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-32041-5_5'
bibtex: '@inbook{Alt_Kenter_Faghih-Naini_Faj_Opdenhövel_Plessl_Aizinger_Hönig_Köstler_2023,
place={Cham}, title={Shallow Water DG Simulations on FPGAs: Design and Comparison
of a Novel Code Generation Pipeline}, DOI={10.1007/978-3-031-32041-5_5},
booktitle={Lecture Notes in Computer Science}, publisher={Springer Nature Switzerland},
author={Alt, Christoph and Kenter, Tobias and Faghih-Naini, Sara and Faj, Jennifer
and Opdenhövel, Jan-Oliver and Plessl, Christian and Aizinger, Vadym and Hönig,
Jan and Köstler, Harald}, year={2023} }'
chicago: 'Alt, Christoph, Tobias Kenter, Sara Faghih-Naini, Jennifer Faj, Jan-Oliver
Opdenhövel, Christian Plessl, Vadym Aizinger, Jan Hönig, and Harald Köstler. “Shallow
Water DG Simulations on FPGAs: Design and Comparison of a Novel Code Generation
Pipeline.” In Lecture Notes in Computer Science. Cham: Springer Nature
Switzerland, 2023. https://doi.org/10.1007/978-3-031-32041-5_5.'
ieee: 'C. Alt et al., “Shallow Water DG Simulations on FPGAs: Design and Comparison
of a Novel Code Generation Pipeline,” in Lecture Notes in Computer Science,
Cham: Springer Nature Switzerland, 2023.'
mla: 'Alt, Christoph, et al. “Shallow Water DG Simulations on FPGAs: Design and Comparison
of a Novel Code Generation Pipeline.” Lecture Notes in Computer Science,
Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-32041-5_5.'
short: 'C. Alt, T. Kenter, S. Faghih-Naini, J. Faj, J.-O. Opdenhövel, C. Plessl,
V. Aizinger, J. Hönig, H. Köstler, in: Lecture Notes in Computer Science, Springer
Nature Switzerland, Cham, 2023.'
date_created: 2023-07-28T09:53:21Z
date_updated: 2024-01-22T09:58:49Z
department:
- _id: '27'
- _id: '518'
doi: 10.1007/978-3-031-32041-5_5
language:
- iso: eng
place: Cham
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Lecture Notes in Computer Science
publication_identifier:
isbn:
- '9783031320408'
- '9783031320415'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
quality_controlled: '1'
status: public
title: 'Shallow Water DG Simulations on FPGAs: Design and Comparison of a Novel Code
Generation Pipeline'
type: book_chapter
user_id: '3145'
year: '2023'
...
---
_id: '51373'
author:
- first_name: Jonas Manuel
full_name: Hanselle, Jonas Manuel
id: '43980'
last_name: Hanselle
orcid: 0000-0002-1231-4985
- first_name: Johannes
full_name: Fürnkranz, Johannes
last_name: Fürnkranz
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Hanselle JM, Fürnkranz J, Hüllermeier E. Probabilistic Scoring Lists for Interpretable
Machine Learning. In: 26th International Conference on Discovery Science .
Vol 14050. Lecture Notes in Computer Science. Springer Nature Switzerland; 2023:189-203.
doi:10.1007/978-3-031-45275-8_13'
apa: Hanselle, J. M., Fürnkranz, J., & Hüllermeier, E. (2023). Probabilistic
Scoring Lists for Interpretable Machine Learning. 26th International Conference
on Discovery Science , 14050, 189–203. https://doi.org/10.1007/978-3-031-45275-8_13
bibtex: '@inproceedings{Hanselle_Fürnkranz_Hüllermeier_2023, place={Cham}, series={Lecture
Notes in Computer Science}, title={Probabilistic Scoring Lists for Interpretable
Machine Learning}, volume={14050}, DOI={10.1007/978-3-031-45275-8_13},
booktitle={26th International Conference on Discovery Science }, publisher={Springer
Nature Switzerland}, author={Hanselle, Jonas Manuel and Fürnkranz, Johannes and
Hüllermeier, Eyke}, year={2023}, pages={189–203}, collection={Lecture Notes in
Computer Science} }'
chicago: 'Hanselle, Jonas Manuel, Johannes Fürnkranz, and Eyke Hüllermeier. “Probabilistic
Scoring Lists for Interpretable Machine Learning.” In 26th International Conference
on Discovery Science , 14050:189–203. Lecture Notes in Computer Science. Cham:
Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-45275-8_13.'
ieee: 'J. M. Hanselle, J. Fürnkranz, and E. Hüllermeier, “Probabilistic Scoring
Lists for Interpretable Machine Learning,” in 26th International Conference
on Discovery Science , Porto, 2023, vol. 14050, pp. 189–203, doi: 10.1007/978-3-031-45275-8_13.'
mla: Hanselle, Jonas Manuel, et al. “Probabilistic Scoring Lists for Interpretable
Machine Learning.” 26th International Conference on Discovery Science ,
vol. 14050, Springer Nature Switzerland, 2023, pp. 189–203, doi:10.1007/978-3-031-45275-8_13.
short: 'J.M. Hanselle, J. Fürnkranz, E. Hüllermeier, in: 26th International Conference
on Discovery Science , Springer Nature Switzerland, Cham, 2023, pp. 189–203.'
conference:
end_date: 2021-10-11
location: Porto
name: '26th International Conference on Discovery Science '
start_date: 2023-10-9
date_created: 2024-02-18T11:05:55Z
date_updated: 2024-02-26T08:41:49Z
doi: 10.1007/978-3-031-45275-8_13
intvolume: ' 14050'
language:
- iso: eng
page: 189-203
place: Cham
publication: '26th International Conference on Discovery Science '
publication_identifier:
isbn:
- '9783031452741'
- '9783031452758'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
series_title: Lecture Notes in Computer Science
status: public
title: Probabilistic Scoring Lists for Interpretable Machine Learning
type: conference
user_id: '54779'
volume: 14050
year: '2023'
...