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Institute for Web Science and Technologies

FB 4: Informatik / Universität Koblenz

Universitatsstrasse 1, 56070 Koblenz
  • 0261/287-2712
Publikationen
Ergebnisse pro Seite:  10

Baris Schlicht, Ipek; Sezerer, Erhan; Tekir, Selma et al.

Leveraging Commonsense Knowledge on Classifying False News and Determining Checkworthiness of Claims.

CoRR. Bd. abs/2108.03731. 2021


Boukhers, Zeyd; Beili, Nada; Hartmann, Timo et al.

MexPub: Deep Transfer Learning for Metadata Extraction from German Publications.

CoRR. Bd. abs/2106.07359. 2021



Kleanthous, Styliani; Otterbacher, Jahna; Bates, Jo et al.

Report on the CyCAT winter school on fairness, accountability, transparency and ethics (FATE) in AI

SIGIR Forum. Bd. 55. H. 1. New York, NY: ACM Association for Computing Machinery 2021 S. 4


Fallatah, Omaima; Zhang, Ziqi; Hopfgartner, Frank

A gold standard dataset for large knowledge graphs matching

Pavel Shvaiko; Jérôme Euzenat; Ernesto Jiménez-Ruiz; Oktie Hassanzadeh; Cássia Trojahn (Hrsg). Proceedings of the 15th International Workshop on Ontology Matching OM 2015: Virtual conference (originally planned to be in Athens, Greece), November 2, 2020. Aachen: CEUR/RWTH 2020 S. 24 - 35


Koltcov, Sergei; Ignatenko, Vera; Boukhers, Zeyd et al.

Analyzing the Influence of Hyper-parameters and Regularizers of Topic Modeling in Terms of Renyi Entropy.

Entropy. Bd. 22. H. 4. 2020 S. 394


Hunter, Anthony; Polberg, Sylwia; Thimm, Matthias

Epistemic graphs for representing and reasoning with positive and negative influences of arguments

Artificial Intelligence. Bd. 281. Amsterdam: Elsevier 2020 S. 103236


Gurrin, Cathal; Joho, Hideo; Hopfgartner, Frank et al.

Experiments in Lifelog Organisation and Retrieval at NTCIR

Tetsuya Sakai; Douglas W. Oard; Noriko Kando (Hrsg). Evaluating Information Retrieval and Access Tasks: NTCIR's Legacy of Research Impact. Singapore: Springer 2020 S. 187 - 203


Hopfgartner, Frank; Joho, Hideo; Gurrin, Cathal

Guest editorial

Online Information Review. Bd. 44. H. 2. Bradford: Emerald 2020 S. 477 - 481


Bates, Jo; Cameron, David; Checco, Alessandro et al.

Integrating FATE/Critical Data Studies into Data Science Curricula: Where are we going and how do we get there?

Mireille Hildebrandt; Carlos Castillo; L. Elisa Celis; Salvatore Ruggieri; Linnet Taylor; Gabriela Zanfir-Fortuna (Hrsg). Proceedings of the FAT* 2020: Conference on Fairness, Accountability, and Transparency; Barcelona, Spain, January 27-30, 2020. New York, NY: ACM Association for Computing Machinery 2020 S. 425 - 435