PUB - Publikationen an der Universität Bielefeld

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• [15]
  

  2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2969356

  H. ter Horst, et al., “Automatic knowledge graph population with model-complete text comprehension for pre-clinical outcomes in the field of spinal cord injury”, Artificial Intelligence in Medicine, vol. 137, 2023, : 102491.

  PUB | DOI | WoS | PubMed | Europe PMC
   
• [14]
  

  2021 | Bielefelder E-Dissertation | PUB-ID: 2959813

  H. ter Horst, Information extraction from text for deep domain knowledge graph population. Extracting pre-clinical outcomes in the domain of spinal cord injury, Bielefeld: Universität Bielefeld, 2021.

  PUB | PDF | DOI
   
• [13]
  

  2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2942743

  H. ter Horst, et al., “Learning soft domain constraints in a factor graph model for template-based information extraction”, DATA & KNOWLEDGE ENGINEERING, vol. 125, 2020, : 101764.

  PUB | DOI | WoS
   
• [12]
  

  2018 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2930952

  H. ter Horst, M. Hartung, and P. Cimiano, “Cold-Start Knowledge Base Population Using Ontology-Based Information Extraction with Conditional Random Fields”, Reasoning Web. Learning, Uncertainty, Streaming, and Scalability., C. d'Amato and M. Theobald, eds., Lecture Notes in Computer Science, vol. 11078, Springer, 2018, pp.78-109.

  PUB | PDF
   
• [11]
  

  2018 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2914075

  A. Schwitteck, H. ter Horst, and M. Hartung, “What Coreference Chains Tell about Experimental Groups in (Pre-)Clinical Trials”, Proceedings of DGfS/CL Poster Session, Stuttgart: 2018.

  PUB | PDF
   
• [10]
  

  2018 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2918981

  H. ter Horst, et al., “Assessing the Impact of Single and Pairwise Slot Constraints in a Factor Graph Model for Template-based Information Extraction”, Proceedings of the 23rd International Conference on Natural Language & Information Systems (NLDB), M. Silberztein, et al., eds., Lecture Notes in Computer Science, vol. 10859, Cham: Springer International Publishing, 2018, pp.179-190.

  PUB | PDF | DOI
   
• [9]
  

  2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2919923

  M. Hartung, et al., “SANTO: A Web-based Annotation Tool for Ontology-driven Slot Filling”, Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (System Demonstrations), Association for Computational Linguistics, 2018.

  PUB | PDF | Download (ext.)
   
• [8]
  

  2017 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2910336

  H. ter Horst, M. Hartung, and P. Cimiano, “Joint Entity Recognition and Linking in Technical Domains Using Undirected Probabilistic Graphical Models”, Language, Data, and Knowledge (Proceedings of the 1st International LDK Conference), J. Gracia, et al., eds., Lecture Notes in Artificial Intelligence, vol. 10318, Springer, 2017, pp.166-180.

  PUB | PDF
   
• [7]
  

  2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2913603

  N. Brazda, et al., “SCIO: An Ontology to Support the Formalization of Pre-Clinical Spinal Cord Injury Experiments”, Proceedings of the 3rd Joint Ontology Workshops (JOWO): Ontologies and Data in the Life Sciences, CEUR Workshop proceedings, vol. 2050, Aachen: RWTH, 2017.

  PUB | PDF | Download (ext.)
   
• [6]
  

  2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2913482

  A. Borowi, et al., “Ontology-driven Visual Exploration of Preclinical Research Data in the Spinal Cord Injury Domain”, Proceedings of the SEMANTICS 2017 Poster and Demo Track, CEUR Workshop proceedings, vol. 2044, Aachen: RWTH, 2017.

  PUB | PDF | Download (ext.)
   
• [5]
  

  2016 | Datenpublikation | PUB-ID: 2902978

  S. Hakimov, et al., Research Data - Combining Textual and Graph-based Features for Named Entity Disambiguation Using Undirected Probabilistic Graphical Models, Bielefeld University, 2016.

  PUB | Dateien verfügbar | DOI
   
• [4]
  

  2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2905552

  S. Hakimov, et al., “Combining Textual and Graph-based Features for Named Entity Disambiguation Using Undirected Probabilistic Graphical Models”, Knowledge Engineering and Knowledge Management, Lecture Notes in Computer Science, vol. 10024, Springer, 2016, pp.288-302.

  PUB | PDF | DOI
   
• [3]
  

  2016 | Diskussionspapier | Veröffentlicht | PUB-ID: 2914039

  H. ter Horst, et al., Predicting Disease-Gene Associations using Cross-Document Graph-based Features, Bielefeld: Bielefeld University, 2016.

  PUB | PDF | arXiv
   
• [2]
  

  2016 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2905448

  N. Brazda, et al., “SCIO: The Spinal Cord Injury Ontology, a Prerequisite for Automated Data Extraction from Publications on Research in Spinal Cord Injury”, Proceedings of the 18th Spinal Research Network Meeting (ISRT 2016), London: 2016.

  PUB
   
• [1]
  

  2015 | Bielefelder Masterarbeit | PUB-ID: 2776749

  H. ter Horst, Ranking of disease gene associations from large corpora of scientific publications, Bielefeld: Bielefeld University, 2015.

  PUB | PDF