---
_id: '29290'
abstract:
- lang: eng
text: "Classifying nodes in knowledge graphs is an important task, e.g., predicting\r\nmissing
types of entities, predicting which molecules cause cancer, or\r\npredicting which
drugs are promising treatment candidates. While black-box\r\nmodels often achieve
high predictive performance, they are only post-hoc and\r\nlocally explainable
and do not allow the learned model to be easily enriched\r\nwith domain knowledge.
Towards this end, learning description logic concepts\r\nfrom positive and negative
examples has been proposed. However, learning such\r\nconcepts often takes a long
time and state-of-the-art approaches provide\r\nlimited support for literal data
values, although they are crucial for many\r\napplications. In this paper, we
propose EvoLearner - an evolutionary approach\r\nto learn ALCQ(D), which is the
attributive language with complement (ALC)\r\npaired with qualified cardinality
restrictions (Q) and data properties (D). We\r\ncontribute a novel initialization
method for the initial population: starting\r\nfrom positive examples (nodes in
the knowledge graph), we perform biased random\r\nwalks and translate them to
description logic concepts. Moreover, we improve\r\nsupport for data properties
by maximizing information gain when deciding where\r\nto split the data. We show
that our approach significantly outperforms the\r\nstate of the art on the benchmarking
framework SML-Bench for structured machine\r\nlearning. Our ablation study confirms
that this is due to our novel\r\ninitialization method and support for data properties."
author:
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Lukas
full_name: Blübaum, Lukas
last_name: Blübaum
- first_name: Nick
full_name: Düsterhus, Nick
last_name: Düsterhus
- first_name: Till
full_name: Werner, Till
last_name: Werner
- first_name: Varun Nandkumar
full_name: Golani, Varun Nandkumar
last_name: Golani
- 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: 'Heindorf S, Blübaum L, Düsterhus N, et al. EvoLearner: Learning Description
Logics with Evolutionary Algorithms. In: WWW. ACM; 2022:818-828. doi:10.1145/3485447.3511925'
apa: 'Heindorf, S., Blübaum, L., Düsterhus, N., Werner, T., Golani, V. N., Demir,
C., & Ngonga Ngomo, A.-C. (2022). EvoLearner: Learning Description Logics
with Evolutionary Algorithms. WWW, 818–828. https://doi.org/10.1145/3485447.3511925'
bibtex: '@inproceedings{Heindorf_Blübaum_Düsterhus_Werner_Golani_Demir_Ngonga Ngomo_2022,
title={EvoLearner: Learning Description Logics with Evolutionary Algorithms},
DOI={10.1145/3485447.3511925},
booktitle={WWW}, publisher={ACM}, author={Heindorf, Stefan and Blübaum, Lukas
and Düsterhus, Nick and Werner, Till and Golani, Varun Nandkumar and Demir, Caglar
and Ngonga Ngomo, Axel-Cyrille}, year={2022}, pages={818–828} }'
chicago: 'Heindorf, Stefan, Lukas Blübaum, Nick Düsterhus, Till Werner, Varun Nandkumar
Golani, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “EvoLearner: Learning Description
Logics with Evolutionary Algorithms.” In WWW, 818–28. ACM, 2022. https://doi.org/10.1145/3485447.3511925.'
ieee: 'S. Heindorf et al., “EvoLearner: Learning Description Logics with
Evolutionary Algorithms,” in WWW, 2022, pp. 818–828, doi: 10.1145/3485447.3511925.'
mla: 'Heindorf, Stefan, et al. “EvoLearner: Learning Description Logics with Evolutionary
Algorithms.” WWW, ACM, 2022, pp. 818–28, doi:10.1145/3485447.3511925.'
short: 'S. Heindorf, L. Blübaum, N. Düsterhus, T. Werner, V.N. Golani, C. Demir,
A.-C. Ngonga Ngomo, in: WWW, ACM, 2022, pp. 818–828.'
date_created: 2022-01-12T10:22:53Z
date_updated: 2024-05-26T19:13:09Z
department:
- _id: '574'
doi: 10.1145/3485447.3511925
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2111.04879
oa: '1'
page: 818-828
publication: WWW
publisher: ACM
status: public
title: 'EvoLearner: Learning Description Logics with Evolutionary Algorithms'
type: conference
user_id: '11871'
year: '2022'
...
---
_id: '29851'
author:
- first_name: 'Svetlana '
full_name: 'Pestryakova, Svetlana '
last_name: Pestryakova
- first_name: Daniel
full_name: Vollmers, Daniel
last_name: Vollmers
- first_name: Mohamed
full_name: Sherif, Mohamed
id: '67234'
last_name: Sherif
orcid: https://orcid.org/0000-0002-9927-2203
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: 'Muhammad '
full_name: 'Saleem, Muhammad '
last_name: Saleem
- 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: 'Pestryakova S, Vollmers D, Sherif M, et al. CovidPubGraph: A FAIR Knowledge
Graph of COVID-19 Publications. Scientific Data. Published online 2022.
doi:10.1038/s41597-022-01298-2'
apa: 'Pestryakova, S., Vollmers, D., Sherif, M., Heindorf, S., Saleem, M., Moussallem,
D., & Ngonga Ngomo, A.-C. (2022). CovidPubGraph: A FAIR Knowledge Graph of
COVID-19 Publications. Scientific Data. https://doi.org/10.1038/s41597-022-01298-2'
bibtex: '@article{Pestryakova_Vollmers_Sherif_Heindorf_Saleem_Moussallem_Ngonga
Ngomo_2022, title={CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications},
DOI={10.1038/s41597-022-01298-2},
journal={Scientific Data}, author={Pestryakova, Svetlana and Vollmers, Daniel
and Sherif, Mohamed and Heindorf, Stefan and Saleem, Muhammad and Moussallem,
Diego and Ngonga Ngomo, Axel-Cyrille}, year={2022} }'
chicago: 'Pestryakova, Svetlana , Daniel Vollmers, Mohamed Sherif, Stefan Heindorf,
Muhammad Saleem, Diego Moussallem, and Axel-Cyrille Ngonga Ngomo. “CovidPubGraph:
A FAIR Knowledge Graph of COVID-19 Publications.” Scientific Data, 2022.
https://doi.org/10.1038/s41597-022-01298-2.'
ieee: 'S. Pestryakova et al., “CovidPubGraph: A FAIR Knowledge Graph of COVID-19
Publications,” Scientific Data, 2022, doi: 10.1038/s41597-022-01298-2.'
mla: 'Pestryakova, Svetlana, et al. “CovidPubGraph: A FAIR Knowledge Graph of COVID-19
Publications.” Scientific Data, 2022, doi:10.1038/s41597-022-01298-2.'
short: S. Pestryakova, D. Vollmers, M. Sherif, S. Heindorf, M. Saleem, D. Moussallem,
A.-C. Ngonga Ngomo, Scientific Data (2022).
date_created: 2022-02-15T16:59:29Z
date_updated: 2024-05-26T19:14:21Z
department:
- _id: '574'
doi: 10.1038/s41597-022-01298-2
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://papers.dice-research.org/2022/NSDJ_CovidPubGraph/public.pdf
oa: '1'
publication: Scientific Data
status: public
title: 'CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications'
type: journal_article
user_id: '11871'
year: '2022'
...
---
_id: '34674'
abstract:
- lang: eng
text: 'Smart home systems contain plenty of features that enhance wellbeing in everyday
life through artificial intelligence (AI). However, many users feel insecure because
they do not understand the AI’s functionality and do not feel they are in control
of it. Combining technical, psychological and philosophical views on AI, we rethink
smart homes as interactive systems where users can partake in an intelligent agent’s
learning. Parallel to the goals of explainable AI (XAI), we explored the possibility
of user involvement in supervised learning of the smart home to have a first approach
to improve acceptance, support subjective understanding and increase perceived
control. In this work, we conducted two studies: In an online pre-study, we asked
participants about their attitude towards teaching AI via a questionnaire. In
the main study, we performed a Wizard of Oz laboratory experiment with human participants,
where participants spent time in a prototypical smart home and taught activity
recognition to the intelligent agent through supervised learning based on the
user’s behaviour. We found that involvement in the AI’s learning phase enhanced
the users’ feeling of control, perceived understanding and perceived usefulness
of AI in general. The participants reported positive attitudes towards training
a smart home AI and found the process understandable and controllable. We suggest
that involving the user in the learning phase could lead to better personalisation
and increased understanding and control by users of intelligent agents for smart
home automation.'
alternative_title:
- Increasing Perceived Control and Understanding
author:
- first_name: Leonie Nora
full_name: Sieger, Leonie Nora
id: '93402'
last_name: Sieger
- first_name: Julia
full_name: Hermann, Julia
last_name: Hermann
- first_name: Astrid
full_name: Schomäcker, Astrid
last_name: Schomäcker
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Christian
full_name: Meske, Christian
last_name: Meske
- first_name: Celine-Chiara
full_name: Hey, Celine-Chiara
last_name: Hey
- first_name: Ayşegül
full_name: Doğangün, Ayşegül
last_name: Doğangün
citation:
ama: 'Sieger LN, Hermann J, Schomäcker A, et al. User Involvement in Training Smart
Home Agents. In: International Conference on Human-Agent Interaction. ACM;
2022. doi:10.1145/3527188.3561914'
apa: 'Sieger, L. N., Hermann, J., Schomäcker, A., Heindorf, S., Meske, C., Hey,
C.-C., & Doğangün, A. (2022). User Involvement in Training Smart Home Agents.
International Conference on Human-Agent Interaction. HAI ’22: International
Conference on Human-Agent Interaction, Christchurch, New Zealand. https://doi.org/10.1145/3527188.3561914'
bibtex: '@inproceedings{Sieger_Hermann_Schomäcker_Heindorf_Meske_Hey_Doğangün_2022,
title={User Involvement in Training Smart Home Agents}, DOI={10.1145/3527188.3561914},
booktitle={International Conference on Human-Agent Interaction}, publisher={ACM},
author={Sieger, Leonie Nora and Hermann, Julia and Schomäcker, Astrid and Heindorf,
Stefan and Meske, Christian and Hey, Celine-Chiara and Doğangün, Ayşegül}, year={2022}
}'
chicago: Sieger, Leonie Nora, Julia Hermann, Astrid Schomäcker, Stefan Heindorf,
Christian Meske, Celine-Chiara Hey, and Ayşegül Doğangün. “User Involvement in
Training Smart Home Agents.” In International Conference on Human-Agent Interaction.
ACM, 2022. https://doi.org/10.1145/3527188.3561914.
ieee: 'L. N. Sieger et al., “User Involvement in Training Smart Home Agents,”
presented at the HAI ’22: International Conference on Human-Agent Interaction,
Christchurch, New Zealand, 2022, doi: 10.1145/3527188.3561914.'
mla: Sieger, Leonie Nora, et al. “User Involvement in Training Smart Home Agents.”
International Conference on Human-Agent Interaction, ACM, 2022, doi:10.1145/3527188.3561914.
short: 'L.N. Sieger, J. Hermann, A. Schomäcker, S. Heindorf, C. Meske, C.-C. Hey,
A. Doğangün, in: International Conference on Human-Agent Interaction, ACM, 2022.'
conference:
end_date: 2022-12-08
location: Christchurch, New Zealand
name: 'HAI ''22: International Conference on Human-Agent Interaction'
start_date: 2022-12-05
date_created: 2022-12-21T09:48:43Z
date_updated: 2024-05-30T18:04:45Z
ddc:
- '000'
department:
- _id: '574'
- _id: '760'
doi: 10.1145/3527188.3561914
file:
- access_level: closed
content_type: application/pdf
creator: heindorf
date_created: 2024-05-30T18:04:31Z
date_updated: 2024-05-30T18:04:31Z
file_id: '54524'
file_name: User_Involvement_in_Training_Smart_Home_Agents_public.pdf
file_size: 1151728
relation: main_file
success: 1
file_date_updated: 2024-05-30T18:04:31Z
has_accepted_license: '1'
keyword:
- human-agent interaction
- smart homes
- supervised learning
- participation
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://papers.dice-research.org/2022/HAI_SmartHome/User_Involvement_in_Training_Smart_Home_Agents_public.pdf
oa: '1'
project:
- _id: '121'
grant_number: '438445824'
name: 'TRR 318 - B1: TRR 318 - Subproject B1'
publication: International Conference on Human-Agent Interaction
publication_status: published
publisher: ACM
quality_controlled: '1'
status: public
title: User Involvement in Training Smart Home Agents
type: conference
user_id: '11871'
year: '2022'
...
---
_id: '33738'
author:
- first_name: Hamada Mohamed Abdelsamee
full_name: Zahera, Hamada Mohamed Abdelsamee
id: '72768'
last_name: Zahera
orcid: 0000-0003-0215-1278
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Stefan
full_name: Balke, Stefan
last_name: Balke
- first_name: Jonas
full_name: Haupt, Jonas
last_name: Haupt
- first_name: Martin
full_name: Voigt, Martin
last_name: Voigt
- first_name: Carolin
full_name: Walter, Carolin
last_name: Walter
- first_name: Fabian
full_name: Witter, Fabian
last_name: Witter
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Zahera HMA, Heindorf S, Balke S, et al. Tab2Onto: Unsupervised Semantification
with Knowledge Graph Embeddings. In: The Semantic Web: ESWC 2022 Satellite
Events. Springer International Publishing; 2022. doi:10.1007/978-3-031-11609-4_9'
apa: 'Zahera, H. M. A., Heindorf, S., Balke, S., Haupt, J., Voigt, M., Walter, C.,
Witter, F., & Ngonga Ngomo, A.-C. (2022). Tab2Onto: Unsupervised Semantification
with Knowledge Graph Embeddings. In The Semantic Web: ESWC 2022 Satellite Events.
Springer International Publishing. https://doi.org/10.1007/978-3-031-11609-4_9'
bibtex: '@inbook{Zahera_Heindorf_Balke_Haupt_Voigt_Walter_Witter_Ngonga Ngomo_2022,
place={Cham}, title={Tab2Onto: Unsupervised Semantification with Knowledge Graph
Embeddings}, DOI={10.1007/978-3-031-11609-4_9},
booktitle={The Semantic Web: ESWC 2022 Satellite Events}, publisher={Springer
International Publishing}, author={Zahera, Hamada Mohamed Abdelsamee and Heindorf,
Stefan and Balke, Stefan and Haupt, Jonas and Voigt, Martin and Walter, Carolin
and Witter, Fabian and Ngonga Ngomo, Axel-Cyrille}, year={2022} }'
chicago: 'Zahera, Hamada Mohamed Abdelsamee, Stefan Heindorf, Stefan Balke, Jonas
Haupt, Martin Voigt, Carolin Walter, Fabian Witter, and Axel-Cyrille Ngonga Ngomo.
“Tab2Onto: Unsupervised Semantification with Knowledge Graph Embeddings.” In The
Semantic Web: ESWC 2022 Satellite Events. Cham: Springer International Publishing,
2022. https://doi.org/10.1007/978-3-031-11609-4_9.'
ieee: 'H. M. A. Zahera et al., “Tab2Onto: Unsupervised Semantification with
Knowledge Graph Embeddings,” in The Semantic Web: ESWC 2022 Satellite Events,
Cham: Springer International Publishing, 2022.'
mla: 'Zahera, Hamada Mohamed Abdelsamee, et al. “Tab2Onto: Unsupervised Semantification
with Knowledge Graph Embeddings.” The Semantic Web: ESWC 2022 Satellite Events,
Springer International Publishing, 2022, doi:10.1007/978-3-031-11609-4_9.'
short: 'H.M.A. Zahera, S. Heindorf, S. Balke, J. Haupt, M. Voigt, C. Walter, F.
Witter, A.-C. Ngonga Ngomo, in: The Semantic Web: ESWC 2022 Satellite Events,
Springer International Publishing, Cham, 2022.'
date_created: 2022-10-15T19:25:42Z
date_updated: 2023-06-23T09:20:20Z
department:
- _id: '574'
doi: 10.1007/978-3-031-11609-4_9
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://2022.eswc-conferences.org/wp-content/uploads/2022/05/pd_Zahera_et_al_paper_230.pdf
oa: '1'
place: Cham
publication: 'The Semantic Web: ESWC 2022 Satellite Events'
publication_identifier:
isbn:
- '9783031116087'
- '9783031116094'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer International Publishing
status: public
title: 'Tab2Onto: Unsupervised Semantification with Knowledge Graph Embeddings'
type: book_chapter
user_id: '72768'
year: '2022'
...
---
_id: '33739'
abstract:
- lang: eng
text: At least 5% of questions submitted to search engines ask about cause-effect
relationships in some way. To support the development of tailored approaches that
can answer such questions, we construct Webis-CausalQA-22, a benchmark corpus
of 1.1 million causal questions with answers. We distinguish different types of
causal questions using a novel typology derived from a data-driven, manual analysis
of questions from ten large question answering (QA) datasets. Using high-precision
lexical rules, we extract causal questions of each type from these datasets to
create our corpus. As an initial baseline, the state-of-the-art QA model UnifiedQA
achieves a ROUGE-L F1 score of 0.48 on our new benchmark.
author:
- first_name: Alexander
full_name: Bondarenko, Alexander
last_name: Bondarenko
- first_name: Magdalena
full_name: Wolska, Magdalena
last_name: Wolska
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Lukas
full_name: Blübaum, Lukas
last_name: Blübaum
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
- first_name: Benno
full_name: Stein, Benno
last_name: Stein
- first_name: Pavel
full_name: Braslavski, Pavel
last_name: Braslavski
- first_name: Matthias
full_name: Hagen, Matthias
last_name: Hagen
- first_name: Martin
full_name: Potthast, Martin
last_name: Potthast
citation:
ama: 'Bondarenko A, Wolska M, Heindorf S, et al. CausalQA: A Benchmark for Causal
Question Answering. In: Proceedings of the 29th International Conference on
Computational Linguistics. International Committee on Computational Linguistics;
2022:3296–3308.'
apa: 'Bondarenko, A., Wolska, M., Heindorf, S., Blübaum, L., Ngonga Ngomo, A.-C.,
Stein, B., Braslavski, P., Hagen, M., & Potthast, M. (2022). CausalQA: A Benchmark
for Causal Question Answering. Proceedings of the 29th International Conference
on Computational Linguistics, 3296–3308.'
bibtex: '@inproceedings{Bondarenko_Wolska_Heindorf_Blübaum_Ngonga Ngomo_Stein_Braslavski_Hagen_Potthast_2022,
place={Gyeongju, Republic of Korea}, title={CausalQA: A Benchmark for Causal Question
Answering}, booktitle={Proceedings of the 29th International Conference on Computational
Linguistics}, publisher={International Committee on Computational Linguistics},
author={Bondarenko, Alexander and Wolska, Magdalena and Heindorf, Stefan and Blübaum,
Lukas and Ngonga Ngomo, Axel-Cyrille and Stein, Benno and Braslavski, Pavel and
Hagen, Matthias and Potthast, Martin}, year={2022}, pages={3296–3308} }'
chicago: 'Bondarenko, Alexander, Magdalena Wolska, Stefan Heindorf, Lukas Blübaum,
Axel-Cyrille Ngonga Ngomo, Benno Stein, Pavel Braslavski, Matthias Hagen, and
Martin Potthast. “CausalQA: A Benchmark for Causal Question Answering.” In Proceedings
of the 29th International Conference on Computational Linguistics, 3296–3308.
Gyeongju, Republic of Korea: International Committee on Computational Linguistics,
2022.'
ieee: 'A. Bondarenko et al., “CausalQA: A Benchmark for Causal Question Answering,”
in Proceedings of the 29th International Conference on Computational Linguistics,
2022, pp. 3296–3308.'
mla: 'Bondarenko, Alexander, et al. “CausalQA: A Benchmark for Causal Question Answering.”
Proceedings of the 29th International Conference on Computational Linguistics,
International Committee on Computational Linguistics, 2022, pp. 3296–3308.'
short: 'A. Bondarenko, M. Wolska, S. Heindorf, L. Blübaum, A.-C. Ngonga Ngomo, B.
Stein, P. Braslavski, M. Hagen, M. Potthast, in: Proceedings of the 29th International
Conference on Computational Linguistics, International Committee on Computational
Linguistics, Gyeongju, Republic of Korea, 2022, pp. 3296–3308.'
date_created: 2022-10-15T19:33:10Z
date_updated: 2023-07-02T18:14:01Z
department:
- _id: '574'
- _id: '760'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://aclanthology.org/2022.coling-1.291.pdf
oa: '1'
page: 3296–3308
place: Gyeongju, Republic of Korea
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Proceedings of the 29th International Conference on Computational Linguistics
publisher: International Committee on Computational Linguistics
status: public
title: 'CausalQA: A Benchmark for Causal Question Answering'
type: conference
user_id: '11871'
year: '2022'
...
---
_id: '29292'
author:
- first_name: Robert
full_name: Feldhans, Robert
last_name: Feldhans
- first_name: Adrian
full_name: Wilke, Adrian
id: '9101'
last_name: Wilke
orcid: 0000-0002-6575-807X
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Mohammad Hossein
full_name: Shaker, Mohammad Hossein
last_name: Shaker
- first_name: Barbara
full_name: Hammer, Barbara
last_name: Hammer
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Feldhans R, Wilke A, Heindorf S, et al. Drift Detection in Text Data with
Document Embeddings. In: Intelligent Data Engineering and Automated Learning
– IDEAL 2021. Springer International Publishing; 2021. doi:10.1007/978-3-030-91608-4_11'
apa: Feldhans, R., Wilke, A., Heindorf, S., Shaker, M. H., Hammer, B., Ngonga Ngomo,
A.-C., & Hüllermeier, E. (2021). Drift Detection in Text Data with Document
Embeddings. In Intelligent Data Engineering and Automated Learning – IDEAL
2021. Springer International Publishing. https://doi.org/10.1007/978-3-030-91608-4_11
bibtex: '@inbook{Feldhans_Wilke_Heindorf_Shaker_Hammer_Ngonga Ngomo_Hüllermeier_2021,
place={Cham}, title={Drift Detection in Text Data with Document Embeddings}, DOI={10.1007/978-3-030-91608-4_11},
booktitle={Intelligent Data Engineering and Automated Learning – IDEAL 2021},
publisher={Springer International Publishing}, author={Feldhans, Robert and Wilke,
Adrian and Heindorf, Stefan and Shaker, Mohammad Hossein and Hammer, Barbara and
Ngonga Ngomo, Axel-Cyrille and Hüllermeier, Eyke}, year={2021} }'
chicago: 'Feldhans, Robert, Adrian Wilke, Stefan Heindorf, Mohammad Hossein Shaker,
Barbara Hammer, Axel-Cyrille Ngonga Ngomo, and Eyke Hüllermeier. “Drift Detection
in Text Data with Document Embeddings.” In Intelligent Data Engineering and
Automated Learning – IDEAL 2021. Cham: Springer International Publishing,
2021. https://doi.org/10.1007/978-3-030-91608-4_11.'
ieee: 'R. Feldhans et al., “Drift Detection in Text Data with Document Embeddings,”
in Intelligent Data Engineering and Automated Learning – IDEAL 2021, Cham:
Springer International Publishing, 2021.'
mla: Feldhans, Robert, et al. “Drift Detection in Text Data with Document Embeddings.”
Intelligent Data Engineering and Automated Learning – IDEAL 2021, Springer
International Publishing, 2021, doi:10.1007/978-3-030-91608-4_11.
short: 'R. Feldhans, A. Wilke, S. Heindorf, M.H. Shaker, B. Hammer, A.-C. Ngonga
Ngomo, E. Hüllermeier, in: Intelligent Data Engineering and Automated Learning
– IDEAL 2021, Springer International Publishing, Cham, 2021.'
date_created: 2022-01-12T10:27:23Z
date_updated: 2022-10-15T19:54:20Z
department:
- _id: '574'
doi: 10.1007/978-3-030-91608-4_11
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://papers.dice-research.org/2021/IDEAL2021_DriftDetectionEmbeddings/Drift-Detection-in-Text-Data-with-Document-Embeddings-public.pdf
oa: '1'
place: Cham
publication: Intelligent Data Engineering and Automated Learning – IDEAL 2021
publication_identifier:
isbn:
- '9783030916077'
- '9783030916084'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer International Publishing
related_material:
link:
- relation: confirmation
url: https://link.springer.com/chapter/10.1007/978-3-030-91608-4_11
status: public
title: Drift Detection in Text Data with Document Embeddings
type: book_chapter
user_id: '11871'
year: '2021'
...
---
_id: '29287'
abstract:
- lang: eng
text: "Knowledge graph embedding research has mainly focused on the two smallest\r\nnormed
division algebras, $\\mathbb{R}$ and $\\mathbb{C}$. Recent results suggest\r\nthat
trilinear products of quaternion-valued embeddings can be a more effective\r\nmeans
to tackle link prediction. In addition, models based on convolutions on\r\nreal-valued
embeddings often yield state-of-the-art results for link\r\nprediction. In this
paper, we investigate a composition of convolution\r\noperations with hypercomplex
multiplications. We propose the four approaches\r\nQMult, OMult, ConvQ and ConvO
to tackle the link prediction problem. QMult and\r\nOMult can be considered as
quaternion and octonion extensions of previous\r\nstate-of-the-art approaches,
including DistMult and ComplEx. ConvQ and ConvO\r\nbuild upon QMult and OMult
by including convolution operations in a way\r\ninspired by the residual learning
framework. We evaluated our approaches on\r\nseven link prediction datasets including
WN18RR, FB15K-237 and YAGO3-10.\r\nExperimental results suggest that the benefits
of learning hypercomplex-valued\r\nvector representations become more apparent
as the size and complexity of the\r\nknowledge graph grows. ConvO outperforms
state-of-the-art approaches on\r\nFB15K-237 in MRR, Hit@1 and Hit@3, while QMult,
OMult, ConvQ and ConvO\r\noutperform state-of-the-approaches on YAGO3-10 in all
metrics. Results also\r\nsuggest that link prediction performances can be further
improved via\r\nprediction averaging. To foster reproducible research, we provide
an\r\nopen-source implementation of approaches, including training and evaluation\r\nscripts
as well as pretrained models."
author:
- first_name: Caglar
full_name: Demir, Caglar
id: '43817'
last_name: Demir
- first_name: Diego
full_name: Moussallem, Diego
id: '71635'
last_name: Moussallem
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Demir C, Moussallem D, Heindorf S, Ngonga Ngomo A-C. Convolutional Hypercomplex
Embeddings for Link Prediction. In: The 13th Asian Conference on Machine Learning,
ACML 2021. ; 2021.'
apa: Demir, C., Moussallem, D., Heindorf, S., & Ngonga Ngomo, A.-C. (2021).
Convolutional Hypercomplex Embeddings for Link Prediction. The 13th Asian Conference
on Machine Learning, ACML 2021.
bibtex: '@inproceedings{Demir_Moussallem_Heindorf_Ngonga Ngomo_2021, title={Convolutional
Hypercomplex Embeddings for Link Prediction}, booktitle={The 13th Asian Conference
on Machine Learning, ACML 2021}, author={Demir, Caglar and Moussallem, Diego and
Heindorf, Stefan and Ngonga Ngomo, Axel-Cyrille}, year={2021} }'
chicago: Demir, Caglar, Diego Moussallem, Stefan Heindorf, and Axel-Cyrille Ngonga
Ngomo. “Convolutional Hypercomplex Embeddings for Link Prediction.” In The
13th Asian Conference on Machine Learning, ACML 2021, 2021.
ieee: C. Demir, D. Moussallem, S. Heindorf, and A.-C. Ngonga Ngomo, “Convolutional
Hypercomplex Embeddings for Link Prediction,” 2021.
mla: Demir, Caglar, et al. “Convolutional Hypercomplex Embeddings for Link Prediction.”
The 13th Asian Conference on Machine Learning, ACML 2021, 2021.
short: 'C. Demir, D. Moussallem, S. Heindorf, A.-C. Ngonga Ngomo, in: The 13th Asian
Conference on Machine Learning, ACML 2021, 2021.'
date_created: 2022-01-12T10:21:10Z
date_updated: 2022-10-17T15:06:40Z
department:
- _id: '574'
external_id:
arxiv:
- '2106.15230'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://papers.dice-research.org/2021/ACML2021_HyperConv/public.pdf
oa: '1'
publication: The 13th Asian Conference on Machine Learning, ACML 2021
status: public
title: Convolutional Hypercomplex Embeddings for Link Prediction
type: conference
user_id: '11871'
year: '2021'
...
---
_id: '29294'
author:
- first_name: Tobias
full_name: Nickchen, Tobias
id: '27340'
last_name: Nickchen
orcid: 0000-0001-8958-9330
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Gregor
full_name: Engels, Gregor
id: '107'
last_name: Engels
citation:
ama: 'Nickchen T, Heindorf S, Engels G. Generating Physically Sound Training Data
for Image Recognition of Additively Manufactured Parts. In: 2021 IEEE Winter
Conference on Applications of Computer Vision (WACV). IEEE; 2021. doi:10.1109/wacv48630.2021.00204'
apa: Nickchen, T., Heindorf, S., & Engels, G. (2021). Generating Physically
Sound Training Data for Image Recognition of Additively Manufactured Parts. 2021
IEEE Winter Conference on Applications of Computer Vision (WACV). https://doi.org/10.1109/wacv48630.2021.00204
bibtex: '@inproceedings{Nickchen_Heindorf_Engels_2021, title={Generating Physically
Sound Training Data for Image Recognition of Additively Manufactured Parts}, DOI={10.1109/wacv48630.2021.00204},
booktitle={2021 IEEE Winter Conference on Applications of Computer Vision (WACV)},
publisher={IEEE}, author={Nickchen, Tobias and Heindorf, Stefan and Engels, Gregor},
year={2021} }'
chicago: Nickchen, Tobias, Stefan Heindorf, and Gregor Engels. “Generating Physically
Sound Training Data for Image Recognition of Additively Manufactured Parts.” In
2021 IEEE Winter Conference on Applications of Computer Vision (WACV).
IEEE, 2021. https://doi.org/10.1109/wacv48630.2021.00204.
ieee: 'T. Nickchen, S. Heindorf, and G. Engels, “Generating Physically Sound Training
Data for Image Recognition of Additively Manufactured Parts,” 2021, doi: 10.1109/wacv48630.2021.00204.'
mla: Nickchen, Tobias, et al. “Generating Physically Sound Training Data for Image
Recognition of Additively Manufactured Parts.” 2021 IEEE Winter Conference
on Applications of Computer Vision (WACV), IEEE, 2021, doi:10.1109/wacv48630.2021.00204.
short: 'T. Nickchen, S. Heindorf, G. Engels, in: 2021 IEEE Winter Conference on
Applications of Computer Vision (WACV), IEEE, 2021.'
date_created: 2022-01-12T10:31:42Z
date_updated: 2022-10-17T15:07:38Z
department:
- _id: '66'
- _id: '574'
doi: 10.1109/wacv48630.2021.00204
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://openaccess.thecvf.com/content/WACV2021/papers/Nickchen_Generating_Physically_Sound_Training_Data_for_Image_Recognition_of_Additively_WACV_2021_paper.pdf
oa: '1'
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: 2021 IEEE Winter Conference on Applications of Computer Vision (WACV)
publication_status: published
publisher: IEEE
status: public
title: Generating Physically Sound Training Data for Image Recognition of Additively
Manufactured Parts
type: conference
user_id: '11871'
year: '2021'
...
---
_id: '33733'
author:
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
citation:
ama: Heindorf S. Automatically generating instructions from tutorials for search
and user navigation. Published online 2021.
apa: Heindorf, S. (2021). Automatically generating instructions from tutorials
for search and user navigation.
bibtex: '@article{Heindorf_2021, title={Automatically generating instructions from
tutorials for search and user navigation}, author={Heindorf, Stefan}, year={2021}
}'
chicago: Heindorf, Stefan. “Automatically Generating Instructions from Tutorials
for Search and User Navigation,” 2021.
ieee: S. Heindorf, “Automatically generating instructions from tutorials for search
and user navigation.” 2021.
mla: Heindorf, Stefan. Automatically Generating Instructions from Tutorials for
Search and User Navigation. 2021.
short: S. Heindorf, (2021).
date_created: 2022-10-15T19:19:10Z
date_updated: 2022-10-17T15:21:49Z
ipc: 'US15/885,363 '
ipn: '10936684'
main_file_link:
- open_access: '1'
url: https://patentimages.storage.googleapis.com/f6/21/79/657191c3dfe93b/US10936684.pdf
oa: '1'
publication_date: 2021-03-02
status: public
title: Automatically generating instructions from tutorials for search and user navigation
type: patent
user_id: '11871'
year: '2021'
...
---
_id: '29291'
author:
- first_name: Hamada Mohamed Abdelsamee
full_name: Zahera, Hamada Mohamed Abdelsamee
id: '72768'
last_name: Zahera
orcid: 0000-0003-0215-1278
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
last_name: Ngonga Ngomo
citation:
ama: 'Zahera HMA, Heindorf S, Ngonga Ngomo A-C. ASSET: A Semi-supervised Approach
for Entity Typing in Knowledge Graphs. In: Proceedings of the 11th on Knowledge
Capture Conference. ACM; 2021. doi:10.1145/3460210.3493563'
apa: 'Zahera, H. M. A., Heindorf, S., & Ngonga Ngomo, A.-C. (2021). ASSET: A
Semi-supervised Approach for Entity Typing in Knowledge Graphs. Proceedings
of the 11th on Knowledge Capture Conference. https://doi.org/10.1145/3460210.3493563'
bibtex: '@inproceedings{Zahera_Heindorf_Ngonga Ngomo_2021, title={ASSET: A Semi-supervised
Approach for Entity Typing in Knowledge Graphs}, DOI={10.1145/3460210.3493563},
booktitle={Proceedings of the 11th on Knowledge Capture Conference}, publisher={ACM},
author={Zahera, Hamada Mohamed Abdelsamee and Heindorf, Stefan and Ngonga Ngomo,
Axel-Cyrille}, year={2021} }'
chicago: 'Zahera, Hamada Mohamed Abdelsamee, Stefan Heindorf, and Axel-Cyrille Ngonga
Ngomo. “ASSET: A Semi-Supervised Approach for Entity Typing in Knowledge Graphs.”
In Proceedings of the 11th on Knowledge Capture Conference. ACM, 2021.
https://doi.org/10.1145/3460210.3493563.'
ieee: 'H. M. A. Zahera, S. Heindorf, and A.-C. Ngonga Ngomo, “ASSET: A Semi-supervised
Approach for Entity Typing in Knowledge Graphs,” 2021, doi: 10.1145/3460210.3493563.'
mla: 'Zahera, Hamada Mohamed Abdelsamee, et al. “ASSET: A Semi-Supervised Approach
for Entity Typing in Knowledge Graphs.” Proceedings of the 11th on Knowledge
Capture Conference, ACM, 2021, doi:10.1145/3460210.3493563.'
short: 'H.M.A. Zahera, S. Heindorf, A.-C. Ngonga Ngomo, in: Proceedings of the 11th
on Knowledge Capture Conference, ACM, 2021.'
date_created: 2022-01-12T10:27:02Z
date_updated: 2024-05-30T18:02:43Z
ddc:
- '000'
department:
- _id: '574'
doi: 10.1145/3460210.3493563
file:
- access_level: closed
content_type: application/pdf
creator: heindorf
date_created: 2024-05-30T18:02:28Z
date_updated: 2024-05-30T18:02:28Z
file_id: '54523'
file_name: ASSET_public.pdf
file_size: 537882
relation: main_file
success: 1
file_date_updated: 2024-05-30T18:02:28Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://papers.dice-research.org/2021/KCAP2021_ASSET/public.pdf
oa: '1'
publication: Proceedings of the 11th on Knowledge Capture Conference
publication_status: published
publisher: ACM
status: public
title: 'ASSET: A Semi-supervised Approach for Entity Typing in Knowledge Graphs'
type: conference
user_id: '11871'
year: '2021'
...
---
_id: '20141'
author:
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Yan
full_name: Scholten, Yan
last_name: Scholten
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
- first_name: Martin
full_name: Potthast, Martin
last_name: Potthast
citation:
ama: 'Heindorf S, Scholten Y, Wachsmuth H, Ngonga Ngomo A-C, Potthast M. CauseNet:
Towards a Causality Graph Extracted from the Web. In: Proceedings of the 28th
ACM International Conference on Information and Knowledge Management (CIKM 2020).
; 2020:3023-3030. doi:10.1145/3340531.3412763'
apa: 'Heindorf, S., Scholten, Y., Wachsmuth, H., Ngonga Ngomo, A.-C., & Potthast,
M. (2020). CauseNet: Towards a Causality Graph Extracted from the Web. Proceedings
of the 28th ACM International Conference on Information and Knowledge Management
(CIKM 2020), 3023–3030. https://doi.org/10.1145/3340531.3412763'
bibtex: '@inproceedings{Heindorf_Scholten_Wachsmuth_Ngonga Ngomo_Potthast_2020,
title={CauseNet: Towards a Causality Graph Extracted from the Web}, DOI={10.1145/3340531.3412763},
booktitle={Proceedings of the 28th ACM International Conference on Information
and Knowledge Management (CIKM 2020)}, author={Heindorf, Stefan and Scholten,
Yan and Wachsmuth, Henning and Ngonga Ngomo, Axel-Cyrille and Potthast, Martin},
year={2020}, pages={3023–3030} }'
chicago: 'Heindorf, Stefan, Yan Scholten, Henning Wachsmuth, Axel-Cyrille Ngonga
Ngomo, and Martin Potthast. “CauseNet: Towards a Causality Graph Extracted from
the Web.” In Proceedings of the 28th ACM International Conference on Information
and Knowledge Management (CIKM 2020), 3023–30, 2020. https://doi.org/10.1145/3340531.3412763.'
ieee: 'S. Heindorf, Y. Scholten, H. Wachsmuth, A.-C. Ngonga Ngomo, and M. Potthast,
“CauseNet: Towards a Causality Graph Extracted from the Web,” in Proceedings
of the 28th ACM International Conference on Information and Knowledge Management
(CIKM 2020), 2020, pp. 3023–3030, doi: 10.1145/3340531.3412763.'
mla: 'Heindorf, Stefan, et al. “CauseNet: Towards a Causality Graph Extracted from
the Web.” Proceedings of the 28th ACM International Conference on Information
and Knowledge Management (CIKM 2020), 2020, pp. 3023–30, doi:10.1145/3340531.3412763.'
short: 'S. Heindorf, Y. Scholten, H. Wachsmuth, A.-C. Ngonga Ngomo, M. Potthast,
in: Proceedings of the 28th ACM International Conference on Information and Knowledge
Management (CIKM 2020), 2020, pp. 3023–3030.'
date_created: 2020-10-20T13:11:14Z
date_updated: 2022-10-15T19:57:01Z
department:
- _id: '574'
doi: 10.1145/3340531.3412763
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://papers.dice-research.org/2020/CIKM-20/heindorf_2020a_public.pdf
oa: '1'
page: 3023-3030
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Proceedings of the 28th ACM International Conference on Information and
Knowledge Management (CIKM 2020)
status: public
title: 'CauseNet: Towards a Causality Graph Extracted from the Web'
type: conference
user_id: '11871'
year: '2020'
...
---
_id: '7668'
author:
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Yan
full_name: Scholten, Yan
last_name: Scholten
- first_name: Gregor
full_name: Engels, Gregor
id: '107'
last_name: Engels
- first_name: Martin
full_name: Potthast, Martin
last_name: Potthast
citation:
ama: 'Heindorf S, Scholten Y, Engels G, Potthast M. Debiasing Vandalism Detection
Models at Wikidata. In: WWW. ACM; 2019:670-680. doi:10.1145/3308558.3313507'
apa: 'Heindorf, S., Scholten, Y., Engels, G., & Potthast, M. (2019). Debiasing
Vandalism Detection Models at Wikidata. In WWW (pp. 670–680). San Francisco,
USA: ACM. https://doi.org/10.1145/3308558.3313507'
bibtex: '@inproceedings{Heindorf_Scholten_Engels_Potthast_2019, title={Debiasing
Vandalism Detection Models at Wikidata}, DOI={10.1145/3308558.3313507},
booktitle={WWW}, publisher={ACM}, author={Heindorf, Stefan and Scholten, Yan and
Engels, Gregor and Potthast, Martin}, year={2019}, pages={670–680} }'
chicago: Heindorf, Stefan, Yan Scholten, Gregor Engels, and Martin Potthast. “Debiasing
Vandalism Detection Models at Wikidata.” In WWW, 670–80. ACM, 2019. https://doi.org/10.1145/3308558.3313507.
ieee: S. Heindorf, Y. Scholten, G. Engels, and M. Potthast, “Debiasing Vandalism
Detection Models at Wikidata,” in WWW, San Francisco, USA, 2019, pp. 670–680.
mla: Heindorf, Stefan, et al. “Debiasing Vandalism Detection Models at Wikidata.”
WWW, ACM, 2019, pp. 670–80, doi:10.1145/3308558.3313507.
short: 'S. Heindorf, Y. Scholten, G. Engels, M. Potthast, in: WWW, ACM, 2019, pp.
670–680.'
conference:
end_date: 2015-05-17
location: San Francisco, USA
name: 2019 World Wide Web Conference (WWW '19)
start_date: 2019-05-13
date_created: 2019-02-13T14:10:36Z
date_updated: 2022-01-06T07:03:43Z
ddc:
- '000'
department:
- _id: '66'
doi: 10.1145/3308558.3313507
file:
- access_level: closed
content_type: application/pdf
creator: heindorf
date_created: 2019-04-27T06:09:45Z
date_updated: 2019-04-27T06:09:45Z
file_id: '9518'
file_name: heindorf2019_WWW.pdf
file_size: 1302648
relation: main_file
success: 1
file_date_updated: 2019-04-27T06:09:45Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/fg-engels/publications_pdfs/Konferenzbeitraege/heindorf2019_WWW.pdf
oa: '1'
page: 670-680
project:
- _id: '17'
name: SFB 901 - Subproject C5
- _id: '4'
name: SFB 901 - Project Area C
- _id: '1'
name: SFB 901
publication: WWW
publication_identifier:
unknown:
- 978-1-4503-6674-8/19/05
publisher: ACM
status: public
title: Debiasing Vandalism Detection Models at Wikidata
type: conference
user_id: '11871'
year: '2019'
...
---
_id: '15333'
author:
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
citation:
ama: Heindorf S. Vandalism Detection in Crowdsourced Knowledge Bases. Universität
Paderborn; 2019.
apa: Heindorf, S. (2019). Vandalism Detection in Crowdsourced Knowledge Bases.
Universität Paderborn.
bibtex: '@book{Heindorf_2019, title={Vandalism Detection in Crowdsourced Knowledge
Bases}, publisher={Universität Paderborn}, author={Heindorf, Stefan}, year={2019}
}'
chicago: Heindorf, Stefan. Vandalism Detection in Crowdsourced Knowledge Bases.
Universität Paderborn, 2019.
ieee: S. Heindorf, Vandalism Detection in Crowdsourced Knowledge Bases. Universität
Paderborn, 2019.
mla: Heindorf, Stefan. Vandalism Detection in Crowdsourced Knowledge Bases.
Universität Paderborn, 2019.
short: S. Heindorf, Vandalism Detection in Crowdsourced Knowledge Bases, Universität
Paderborn, 2019.
date_created: 2019-12-17T06:15:38Z
date_updated: 2022-01-06T06:52:20Z
ddc:
- '040'
department:
- _id: '66'
file:
- access_level: closed
content_type: application/pdf
creator: florida
date_created: 2020-01-16T12:09:52Z
date_updated: 2020-01-16T12:09:52Z
file_id: '15603'
file_name: Dissertation_Stefan_Heindorf.pdf
file_size: 1740910
relation: main_file
success: 1
file_date_updated: 2020-01-16T12:09:52Z
has_accepted_license: '1'
language:
- iso: eng
project:
- _id: '1'
name: SFB 901
- _id: '4'
name: SFB 901 - Project Area C
- _id: '17'
name: SFB 901 - Subproject C5
publisher: Universität Paderborn
status: public
supervisor:
- first_name: Gregor
full_name: Engels, Gregor
id: '107'
last_name: Engels
title: Vandalism Detection in Crowdsourced Knowledge Bases
type: dissertation
user_id: '477'
year: '2019'
...
---
_id: '14568'
author:
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Yan
full_name: Scholten, Yan
last_name: Scholten
- first_name: Gregor
full_name: Engels, Gregor
id: '107'
last_name: Engels
- first_name: Martin
full_name: Potthast, Martin
last_name: Potthast
citation:
ama: 'Heindorf S, Scholten Y, Engels G, Potthast M. Debiasing Vandalism Detection
Models at Wikidata (Extended Abstract). In: INFORMATIK. ; 2019:289-290.
doi:10.18420/inf2019_48'
apa: Heindorf, S., Scholten, Y., Engels, G., & Potthast, M. (2019). Debiasing
Vandalism Detection Models at Wikidata (Extended Abstract). In INFORMATIK
(pp. 289–290). https://doi.org/10.18420/inf2019_48
bibtex: '@inproceedings{Heindorf_Scholten_Engels_Potthast_2019, title={Debiasing
Vandalism Detection Models at Wikidata (Extended Abstract)}, DOI={10.18420/inf2019_48},
booktitle={INFORMATIK}, author={Heindorf, Stefan and Scholten, Yan and Engels,
Gregor and Potthast, Martin}, year={2019}, pages={289–290} }'
chicago: Heindorf, Stefan, Yan Scholten, Gregor Engels, and Martin Potthast. “Debiasing
Vandalism Detection Models at Wikidata (Extended Abstract).” In INFORMATIK,
289–90, 2019. https://doi.org/10.18420/inf2019_48.
ieee: S. Heindorf, Y. Scholten, G. Engels, and M. Potthast, “Debiasing Vandalism
Detection Models at Wikidata (Extended Abstract),” in INFORMATIK, 2019,
pp. 289–290.
mla: Heindorf, Stefan, et al. “Debiasing Vandalism Detection Models at Wikidata
(Extended Abstract).” INFORMATIK, 2019, pp. 289–90, doi:10.18420/inf2019_48.
short: 'S. Heindorf, Y. Scholten, G. Engels, M. Potthast, in: INFORMATIK, 2019,
pp. 289–290.'
date_created: 2019-11-05T15:48:52Z
date_updated: 2022-01-06T06:52:03Z
department:
- _id: '66'
doi: 10.18420/inf2019_48
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://dl.gi.de/bitstream/handle/20.500.12116/24997/paper3_25.pdf
oa: '1'
page: 289-290
publication: INFORMATIK
status: public
title: Debiasing Vandalism Detection Models at Wikidata (Extended Abstract)
type: conference
user_id: '11871'
year: '2019'
...
---
_id: '5831'
abstract:
- lang: eng
text: Many websites offer links to social media sites for convenient content sharing.
Unfortunately, those sharing capabilities are quite restricted and it is seldom
possible to share content with other services, like those provided by a user's
favorite applications or smart devices. In this paper, we present Semantic Data
Mediator (SDM) --- a flexible middleware linking a vast number of services to
millions of websites. Based on reusable repositories of service descriptions defined
by the crowd, users can easily fill a personal registry with their favorite services,
which can then be linked to websites by SDM. For this, SDM leverages semantic
data, which is already available on millions of websites due to search engine
optimization. Further support for our approach from website or service developers
is not required. To enable the use of a broad range of services, data conversion
services are automatically composed by SDM to transform data according to the
needs of the different services. In addition to linking web services, various
service adapters allow services of applications and smart devices to be linked
as well. We have fully implemented our approach and present a real-world case
study demonstrating its feasibility and usefulness.
author:
- first_name: Dennis
full_name: Wolters, Dennis
id: '11308'
last_name: Wolters
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Jonas
full_name: Kirchhoff, Jonas
id: '39928'
last_name: Kirchhoff
- first_name: Gregor
full_name: Engels, Gregor
id: '107'
last_name: Engels
citation:
ama: 'Wolters D, Heindorf S, Kirchhoff J, Engels G. Semantic Data Mediator: Linking
Services to Websites. In: Braubach L, Murillo JM, Kaviani N, et al., eds. Service-Oriented
Computing -- ICSOC 2017 Workshops. Springer International Publishing; 2018:388-392.
doi:10.1007/978-3-319-91764-1_36'
apa: 'Wolters, D., Heindorf, S., Kirchhoff, J., & Engels, G. (2018). Semantic
Data Mediator: Linking Services to Websites. In L. Braubach, J. M. Murillo, N.
Kaviani, M. Lama, L. Burgueño, N. Moha, & M. Oriol (Eds.), Service-Oriented
Computing -- ICSOC 2017 Workshops (pp. 388–392). Springer International Publishing.
https://doi.org/10.1007/978-3-319-91764-1_36'
bibtex: '@inproceedings{Wolters_Heindorf_Kirchhoff_Engels_2018, place={Cham}, title={Semantic
Data Mediator: Linking Services to Websites}, DOI={10.1007/978-3-319-91764-1_36},
booktitle={Service-Oriented Computing -- ICSOC 2017 Workshops}, publisher={Springer
International Publishing}, author={Wolters, Dennis and Heindorf, Stefan and Kirchhoff,
Jonas and Engels, Gregor}, editor={Braubach, Lars and Murillo, Juan M. and Kaviani,
Nima and Lama, Manuel and Burgueño, Loli and Moha, Naouel and Oriol, Marc}, year={2018},
pages={388–392} }'
chicago: 'Wolters, Dennis, Stefan Heindorf, Jonas Kirchhoff, and Gregor Engels.
“Semantic Data Mediator: Linking Services to Websites.” In Service-Oriented
Computing -- ICSOC 2017 Workshops, edited by Lars Braubach, Juan M. Murillo,
Nima Kaviani, Manuel Lama, Loli Burgueño, Naouel Moha, and Marc Oriol, 388–92.
Cham: Springer International Publishing, 2018. https://doi.org/10.1007/978-3-319-91764-1_36.'
ieee: 'D. Wolters, S. Heindorf, J. Kirchhoff, and G. Engels, “Semantic Data Mediator:
Linking Services to Websites,” in Service-Oriented Computing -- ICSOC 2017
Workshops, 2018, pp. 388–392, doi: 10.1007/978-3-319-91764-1_36.'
mla: 'Wolters, Dennis, et al. “Semantic Data Mediator: Linking Services to Websites.”
Service-Oriented Computing -- ICSOC 2017 Workshops, edited by Lars Braubach
et al., Springer International Publishing, 2018, pp. 388–92, doi:10.1007/978-3-319-91764-1_36.'
short: 'D. Wolters, S. Heindorf, J. Kirchhoff, G. Engels, in: L. Braubach, J.M.
Murillo, N. Kaviani, M. Lama, L. Burgueño, N. Moha, M. Oriol (Eds.), Service-Oriented
Computing -- ICSOC 2017 Workshops, Springer International Publishing, Cham, 2018,
pp. 388–392.'
date_created: 2018-11-26T11:52:59Z
date_updated: 2022-10-15T20:00:17Z
department:
- _id: '66'
doi: 10.1007/978-3-319-91764-1_36
editor:
- first_name: Lars
full_name: Braubach, Lars
last_name: Braubach
- first_name: Juan M.
full_name: Murillo, Juan M.
last_name: Murillo
- first_name: Nima
full_name: Kaviani, Nima
last_name: Kaviani
- first_name: Manuel
full_name: Lama, Manuel
last_name: Lama
- first_name: Loli
full_name: Burgueño, Loli
last_name: Burgueño
- first_name: Naouel
full_name: Moha, Naouel
last_name: Moha
- first_name: Marc
full_name: Oriol, Marc
last_name: Oriol
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/fg-engels/publications_pdfs/Konferenzbeitraege/wolters2017_ICSOC_demo.pdf
oa: '1'
page: 388-392
place: Cham
publication: Service-Oriented Computing -- ICSOC 2017 Workshops
publication_identifier:
isbn:
- 978-3-319-91764-1
publisher: Springer International Publishing
status: public
title: 'Semantic Data Mediator: Linking Services to Websites'
type: conference
user_id: '11871'
year: '2018'
...
---
_id: '5829'
abstract:
- lang: eng
text: Websites increasingly embed semantic data for search engine optimization.
The most common ontology for semantic data, schema.org, is supported by all major
search engines and describes over 500 data types, including calendar events, recipes,
products, and TV shows. As of today, users wishing to pass this data to their
favorite applications, e.g., their calendars, cookbooks, price comparison applications
or even smart devices such as TV receivers, rely on cumbersome and error-prone
workarounds such as reentering the data or a series of copy and paste operations.
In this paper, we present Semantic Data Mediator (SDM), an approach that allows
the easy transfer of semantic data to a multitude of services, ranging from web
services to applications installed on different devices. SDM extracts semantic
data from the currently displayed web page on the client-side, offers suitable
services to the user, and by the press of a button, forwards this data to the
desired service while doing all the necessary data conversion and service interface
adaptation in between. To realize this, we built a reusable repository of service
descriptions, data converters, and service adapters, which can be extended by
the crowd. Our approach for linking services to websites relies solely on semantic
data and does not require any additional support by either website or service
developers. We have fully implemented our approach and present a real-world case
study demonstrating its feasibility and usefulness.
author:
- first_name: Dennis
full_name: Wolters, Dennis
id: '11308'
last_name: Wolters
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Jonas
full_name: Kirchhoff, Jonas
id: '39928'
last_name: Kirchhoff
- first_name: Gregor
full_name: Engels, Gregor
id: '107'
last_name: Engels
citation:
ama: 'Wolters D, Heindorf S, Kirchhoff J, Engels G. Linking Services to Websites
by Leveraging Semantic Data. In: Altintas I, Chen S, eds. 2017 IEEE International
Conference on Web Services (ICWS). IEEE; 2017. doi:10.1109/icws.2017.80'
apa: Wolters, D., Heindorf, S., Kirchhoff, J., & Engels, G. (2017). Linking
Services to Websites by Leveraging Semantic Data. In I. Altintas & S. Chen
(Eds.), 2017 IEEE International Conference on Web Services (ICWS). IEEE.
https://doi.org/10.1109/icws.2017.80
bibtex: '@inproceedings{Wolters_Heindorf_Kirchhoff_Engels_2017, title={Linking Services
to Websites by Leveraging Semantic Data}, DOI={10.1109/icws.2017.80},
booktitle={2017 IEEE International Conference on Web Services (ICWS)}, publisher={IEEE},
author={Wolters, Dennis and Heindorf, Stefan and Kirchhoff, Jonas and Engels,
Gregor}, editor={Altintas, Ilkay and Chen, Shiping}, year={2017} }'
chicago: Wolters, Dennis, Stefan Heindorf, Jonas Kirchhoff, and Gregor Engels. “Linking
Services to Websites by Leveraging Semantic Data.” In 2017 IEEE International
Conference on Web Services (ICWS), edited by Ilkay Altintas and Shiping Chen.
IEEE, 2017. https://doi.org/10.1109/icws.2017.80.
ieee: 'D. Wolters, S. Heindorf, J. Kirchhoff, and G. Engels, “Linking Services to
Websites by Leveraging Semantic Data,” in 2017 IEEE International Conference
on Web Services (ICWS), 2017, doi: 10.1109/icws.2017.80.'
mla: Wolters, Dennis, et al. “Linking Services to Websites by Leveraging Semantic
Data.” 2017 IEEE International Conference on Web Services (ICWS), edited
by Ilkay Altintas and Shiping Chen, IEEE, 2017, doi:10.1109/icws.2017.80.
short: 'D. Wolters, S. Heindorf, J. Kirchhoff, G. Engels, in: I. Altintas, S. Chen
(Eds.), 2017 IEEE International Conference on Web Services (ICWS), IEEE, 2017.'
date_created: 2018-11-26T11:49:31Z
date_updated: 2022-10-15T20:01:55Z
department:
- _id: '66'
doi: 10.1109/icws.2017.80
editor:
- first_name: Ilkay
full_name: Altintas, Ilkay
last_name: Altintas
- first_name: Shiping
full_name: Chen, Shiping
last_name: Chen
keyword:
- Services
- Websites
- Semantic Data
- schema.org
- Data Conversion
- Interface Adaptation
- Mediation
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://cs.uni-paderborn.de/fileadmin/informatik/fg/dbis/Publikationen/2017/wolters2017_ICWS.pdf
oa: '1'
publication: 2017 IEEE International Conference on Web Services (ICWS)
publication_identifier:
isbn:
- '9781538607527'
publication_status: published
publisher: IEEE
status: public
title: Linking Services to Websites by Leveraging Semantic Data
type: conference
user_id: '11871'
year: '2017'
...
---
_id: '6722'
abstract:
- lang: eng
text: "We report on the Wikidata vandalism detection task at the WSDM Cup 2017.
The\r\ntask received five submissions for which this paper describes their evaluation\r\nand
a comparison to state of the art baselines. Unlike previous work, we recast\r\nWikidata
vandalism detection as an online learning problem, requiring\r\nparticipant software
to predict vandalism in near real-time. The\r\nbest-performing approach achieves
a ROC-AUC of 0.947 at a PR-AUC of 0.458. In\r\nparticular, this task was organized
as a software submission task: to maximize\r\nreproducibility as well as to foster
future research and development on this\r\ntask, the participants were asked to
submit their working software to the TIRA\r\nexperimentation platform along with
the source code for open source release."
author:
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Martin
full_name: Potthast, Martin
last_name: Potthast
- first_name: Gregor
full_name: Engels, Gregor
id: '107'
last_name: Engels
- first_name: Benno
full_name: Stein, Benno
last_name: Stein
citation:
ama: 'Heindorf S, Potthast M, Engels G, Stein B. Overview of the Wikidata Vandalism
Detection Task at WSDM Cup 2017. In: WSDM Cup 2017 Notebook Papers. ; 2017.'
apa: Heindorf, S., Potthast, M., Engels, G., & Stein, B. (2017). Overview of
the Wikidata Vandalism Detection Task at WSDM Cup 2017. WSDM Cup 2017 Notebook
Papers.
bibtex: '@inproceedings{Heindorf_Potthast_Engels_Stein_2017, title={Overview of
the Wikidata Vandalism Detection Task at WSDM Cup 2017}, booktitle={WSDM Cup 2017
Notebook Papers}, author={Heindorf, Stefan and Potthast, Martin and Engels, Gregor
and Stein, Benno}, year={2017} }'
chicago: Heindorf, Stefan, Martin Potthast, Gregor Engels, and Benno Stein. “Overview
of the Wikidata Vandalism Detection Task at WSDM Cup 2017.” In WSDM Cup 2017
Notebook Papers, 2017.
ieee: S. Heindorf, M. Potthast, G. Engels, and B. Stein, “Overview of the Wikidata
Vandalism Detection Task at WSDM Cup 2017,” 2017.
mla: Heindorf, Stefan, et al. “Overview of the Wikidata Vandalism Detection Task
at WSDM Cup 2017.” WSDM Cup 2017 Notebook Papers, 2017.
short: 'S. Heindorf, M. Potthast, G. Engels, B. Stein, in: WSDM Cup 2017 Notebook
Papers, 2017.'
date_created: 2019-01-15T08:57:40Z
date_updated: 2022-10-17T11:36:12Z
department:
- _id: '66'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1712.05956
oa: '1'
publication: WSDM Cup 2017 Notebook Papers
status: public
title: Overview of the Wikidata Vandalism Detection Task at WSDM Cup 2017
type: conference
user_id: '11871'
year: '2017'
...
---
_id: '33732'
abstract:
- lang: eng
text: "The WSDM Cup 2017 was a data mining challenge held in conjunction with the\r\n10th
International Conference on Web Search and Data Mining (WSDM). It\r\naddressed
key challenges of knowledge bases today: quality assurance and entity\r\nsearch.
For quality assurance, we tackle the task of vandalism detection, based\r\non
a dataset of more than 82 million user-contributed revisions of the Wikidata\r\nknowledge
base, all of which annotated with regard to whether or not they are\r\nvandalism.
For entity search, we tackle the task of triple scoring, using a\r\ndataset that
comprises relevance scores for triples from type-like relations\r\nincluding occupation
and country of citizenship, based on about 10,000 human\r\nrelevance judgements.
For reproducibility sake, participants were asked to\r\nsubmit their software
on TIRA, a cloud-based evaluation platform, and they were\r\nincentivized to share
their approaches open source."
author:
- first_name: Martin
full_name: Potthast, Martin
last_name: Potthast
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Hannah
full_name: Bast, Hannah
last_name: Bast
citation:
ama: 'Potthast M, Heindorf S, Bast H. Proceedings of the WSDM Cup 2017: Vandalism
Detection and Triple Scoring. arXiv:171209528. Published online 2017.'
apa: 'Potthast, M., Heindorf, S., & Bast, H. (2017). Proceedings of the WSDM
Cup 2017: Vandalism Detection and Triple Scoring. In arXiv:1712.09528.'
bibtex: '@article{Potthast_Heindorf_Bast_2017, title={Proceedings of the WSDM Cup
2017: Vandalism Detection and Triple Scoring}, journal={arXiv:1712.09528}, author={Potthast,
Martin and Heindorf, Stefan and Bast, Hannah}, year={2017} }'
chicago: 'Potthast, Martin, Stefan Heindorf, and Hannah Bast. “Proceedings of the
WSDM Cup 2017: Vandalism Detection and Triple Scoring.” ArXiv:1712.09528,
2017.'
ieee: 'M. Potthast, S. Heindorf, and H. Bast, “Proceedings of the WSDM Cup 2017:
Vandalism Detection and Triple Scoring,” arXiv:1712.09528. 2017.'
mla: 'Potthast, Martin, et al. “Proceedings of the WSDM Cup 2017: Vandalism Detection
and Triple Scoring.” ArXiv:1712.09528, 2017.'
short: M. Potthast, S. Heindorf, H. Bast, ArXiv:1712.09528 (2017).
date_created: 2022-10-15T19:14:01Z
date_updated: 2022-10-17T11:21:00Z
department:
- _id: '66'
external_id:
arxiv:
- '1712.09528'
language:
- iso: eng
publication: arXiv:1712.09528
status: public
title: 'Proceedings of the WSDM Cup 2017: Vandalism Detection and Triple Scoring'
type: preprint
user_id: '11871'
year: '2017'
...
---
_id: '6721'
author:
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Martin
full_name: Potthast, Martin
last_name: Potthast
- first_name: Hannah
full_name: Bast, Hannah
last_name: Bast
- first_name: Björn
full_name: Buchhold, Björn
last_name: Buchhold
- first_name: Elmar
full_name: Haussmann, Elmar
last_name: Haussmann
citation:
ama: 'Heindorf S, Potthast M, Bast H, Buchhold B, Haussmann E. WSDM Cup 2017: Vandalism
Detection and Triple Scoring. In: WSDM. ACM; 2017:827-828. doi:10.1145/3018661.3022762'
apa: 'Heindorf, S., Potthast, M., Bast, H., Buchhold, B., & Haussmann, E. (2017).
WSDM Cup 2017: Vandalism Detection and Triple Scoring. WSDM, 827–828. https://doi.org/10.1145/3018661.3022762'
bibtex: '@inproceedings{Heindorf_Potthast_Bast_Buchhold_Haussmann_2017, title={WSDM
Cup 2017: Vandalism Detection and Triple Scoring}, DOI={10.1145/3018661.3022762},
booktitle={WSDM}, publisher={ACM}, author={Heindorf, Stefan and Potthast, Martin
and Bast, Hannah and Buchhold, Björn and Haussmann, Elmar}, year={2017}, pages={827–828}
}'
chicago: 'Heindorf, Stefan, Martin Potthast, Hannah Bast, Björn Buchhold, and Elmar
Haussmann. “WSDM Cup 2017: Vandalism Detection and Triple Scoring.” In WSDM,
827–28. ACM, 2017. https://doi.org/10.1145/3018661.3022762.'
ieee: 'S. Heindorf, M. Potthast, H. Bast, B. Buchhold, and E. Haussmann, “WSDM Cup
2017: Vandalism Detection and Triple Scoring,” in WSDM, 2017, pp. 827–828,
doi: 10.1145/3018661.3022762.'
mla: 'Heindorf, Stefan, et al. “WSDM Cup 2017: Vandalism Detection and Triple Scoring.”
WSDM, ACM, 2017, pp. 827–28, doi:10.1145/3018661.3022762.'
short: 'S. Heindorf, M. Potthast, H. Bast, B. Buchhold, E. Haussmann, in: WSDM,
ACM, 2017, pp. 827–828.'
date_created: 2019-01-15T08:54:23Z
date_updated: 2024-05-26T19:15:24Z
department:
- _id: '66'
doi: 10.1145/3018661.3022762
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://cs.uni-paderborn.de/fileadmin/informatik/fg/dbis/Publikationen/2017/heindorf2017_WSDM.pdf
oa: '1'
page: 827-828
publication: WSDM
publisher: ACM
status: public
title: 'WSDM Cup 2017: Vandalism Detection and Triple Scoring'
type: conference
user_id: '11871'
year: '2017'
...
---
_id: '137'
abstract:
- lang: eng
text: Wikidata is the new, large-scale knowledge base of the Wikimedia Foundation.
Its knowledge is increasingly used within Wikipedia itself and various other kinds
of information systems, imposing high demands on its integrity.Wikidata can be
edited by anyone and, unfortunately, it frequently gets vandalized, exposing all
information systems using it to the risk of spreading vandalized and falsified
information. In this paper, we present a new machine learning-based approach to
detect vandalism in Wikidata.We propose a set of 47 features that exploit both
content and context information, and we report on 4 classifiers of increasing
effectiveness tailored to this learning task. Our approach is evaluated on the
recently published Wikidata Vandalism Corpus WDVC-2015 and it achieves an area
under curve value of the receiver operating characteristic, ROC-AUC, of 0.991.
It significantly outperforms the state of the art represented by the rule-based
Wikidata Abuse Filter (0.865 ROC-AUC) and a prototypical vandalism detector recently
introduced by Wikimedia within the Objective Revision Evaluation Service (0.859
ROC-AUC).
author:
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Matthias
full_name: Potthast, Matthias
last_name: Potthast
- first_name: Benno
full_name: Stein, Benno
last_name: Stein
- first_name: Gregor
full_name: Engels, Gregor
id: '107'
last_name: Engels
citation:
ama: 'Heindorf S, Potthast M, Stein B, Engels G. Vandalism Detection in Wikidata.
In: Proceedings of the 25th International Conference on Information and Knowledge
Management (CIKM 2016). ; 2016:327--336. doi:10.1145/2983323.2983740'
apa: Heindorf, S., Potthast, M., Stein, B., & Engels, G. (2016). Vandalism Detection
in Wikidata. Proceedings of the 25th International Conference on Information
and Knowledge Management (CIKM 2016), 327--336. https://doi.org/10.1145/2983323.2983740
bibtex: '@inproceedings{Heindorf_Potthast_Stein_Engels_2016, title={Vandalism Detection
in Wikidata}, DOI={10.1145/2983323.2983740},
booktitle={Proceedings of the 25th International Conference on Information and
Knowledge Management (CIKM 2016)}, author={Heindorf, Stefan and Potthast, Matthias
and Stein, Benno and Engels, Gregor}, year={2016}, pages={327--336} }'
chicago: Heindorf, Stefan, Matthias Potthast, Benno Stein, and Gregor Engels. “Vandalism
Detection in Wikidata.” In Proceedings of the 25th International Conference
on Information and Knowledge Management (CIKM 2016), 327--336, 2016. https://doi.org/10.1145/2983323.2983740.
ieee: 'S. Heindorf, M. Potthast, B. Stein, and G. Engels, “Vandalism Detection in
Wikidata,” in Proceedings of the 25th International Conference on Information
and Knowledge Management (CIKM 2016), 2016, pp. 327--336, doi: 10.1145/2983323.2983740.'
mla: Heindorf, Stefan, et al. “Vandalism Detection in Wikidata.” Proceedings
of the 25th International Conference on Information and Knowledge Management (CIKM
2016), 2016, pp. 327--336, doi:10.1145/2983323.2983740.
short: 'S. Heindorf, M. Potthast, B. Stein, G. Engels, in: Proceedings of the 25th
International Conference on Information and Knowledge Management (CIKM 2016),
2016, pp. 327--336.'
date_created: 2017-10-17T12:41:18Z
date_updated: 2022-10-17T11:31:41Z
ddc:
- '040'
department:
- _id: '66'
doi: 10.1145/2983323.2983740
file:
- access_level: closed
content_type: application/pdf
creator: florida
date_created: 2018-03-21T13:01:43Z
date_updated: 2018-03-21T13:01:43Z
file_id: '1561'
file_name: 137-p327-heindorf.pdf
file_size: 1842753
relation: main_file
success: 1
file_date_updated: 2018-03-21T13:01:43Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/fg-engels/publications_pdfs/Konferenzbeitraege/heindorf2016_CIKM.pdf
oa: '1'
page: 327--336
project:
- _id: '1'
name: SFB 901
- _id: '17'
name: SFB 901 - Subprojekt C5
- _id: '4'
name: SFB 901 - Project Area C
publication: Proceedings of the 25th International Conference on Information and Knowledge
Management (CIKM 2016)
status: public
title: Vandalism Detection in Wikidata
type: conference
user_id: '11871'
year: '2016'
...