13 Publikationen

Alle markieren

[13]
2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2942743
ter Horst, H., et al., 2020. Learning soft domain constraints in a factor graph model for template-based information extraction. DATA & KNOWLEDGE ENGINEERING, 125: 101764.
PUB | DOI | WoS
 
[12]
2018 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2930952 OA
ter Horst, H., Hartung, M., & Cimiano, P., 2018. Cold-Start Knowledge Base Population Using Ontology-Based Information Extraction with Conditional Random Fields. In C. d'Amato & M. Theobald, eds. Reasoning Web. Learning, Uncertainty, Streaming, and Scalability. Lecture Notes in Computer Science. no.11078 Springer, pp. 78-109.
PUB | PDF
 
[11]
2018 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2914075 OA
Schwitteck, A., ter Horst, H., & Hartung, M., 2018. What Coreference Chains Tell about Experimental Groups in (Pre-)Clinical Trials. In Proceedings of DGfS/CL Poster Session. Stuttgart.
PUB | PDF
 
[10]
2018 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2918981 OA
ter Horst, H., et al., 2018. Assessing the Impact of Single and Pairwise Slot Constraints in a Factor Graph Model for Template-based Information Extraction. In M. Silberztein, et al., eds. Proceedings of the 23rd International Conference on Natural Language & Information Systems (NLDB). Lecture Notes in Computer Science. no.10859 Cham: Springer International Publishing, pp. 179-190.
PUB | PDF | DOI
 
[9]
2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2919923 OA
Hartung, M., et al., 2018. SANTO: A Web-based Annotation Tool for Ontology-driven Slot Filling. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (System Demonstrations). Association for Computational Linguistics.
PUB | PDF | Download (ext.)
 
[8]
2017 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2910336 OA
ter Horst, H., Hartung, M., & Cimiano, P., 2017. Joint Entity Recognition and Linking in Technical Domains Using Undirected Probabilistic Graphical Models. In J. Gracia, et al., eds. Language, Data, and Knowledge (Proceedings of the 1st International LDK Conference). Lecture Notes in Artificial Intelligence. no.10318 Springer, pp. 166-180.
PUB | PDF
 
[7]
2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2913482 OA
Borowi, A., et al., 2017. Ontology-driven Visual Exploration of Preclinical Research Data in the Spinal Cord Injury Domain. In Proceedings of the SEMANTICS 2017 Poster and Demo Track. CEUR Workshop proceedings. no.2044 Aachen: RWTH.
PUB | PDF | Download (ext.)
 
[6]
2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2913603 OA
Brazda, N., et al., 2017. SCIO: An Ontology to Support the Formalization of Pre-Clinical Spinal Cord Injury Experiments. In Proceedings of the 3rd Joint Ontology Workshops (JOWO): Ontologies and Data in the Life Sciences. CEUR Workshop proceedings. no.2050 Aachen: RWTH.
PUB | PDF | Download (ext.)
 
[5]
2016 | Datenpublikation | PUB-ID: 2902978 OA
Hakimov, S., et al., 2016. Research Data - Combining Textual and Graph-based Features for Named Entity Disambiguation Using Undirected Probabilistic Graphical Models, Bielefeld University.
PUB | Dateien verfügbar | DOI
 
[4]
2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2905552 OA
Hakimov, S., et al., 2016. Combining Textual and Graph-based Features for Named Entity Disambiguation Using Undirected Probabilistic Graphical Models. In Knowledge Engineering and Knowledge Management. Lecture Notes in Computer Science. no.10024 Springer, pp. 288-302.
PUB | PDF | DOI
 
[3]
2016 | Diskussionspapier | Veröffentlicht | PUB-ID: 2914039 OA
ter Horst, H., et al., 2016. Predicting Disease-Gene Associations using Cross-Document Graph-based Features, Bielefeld: Bielefeld University.
PUB | PDF | arXiv
 
[2]
2016 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2905448
Brazda, N., et al., 2016. SCIO: The Spinal Cord Injury Ontology, a Prerequisite for Automated Data Extraction from Publications on Research in Spinal Cord Injury. In Proceedings of the 18th Spinal Research Network Meeting (ISRT 2016). London.
PUB
 
[1]
2015 | Bielefelder Masterarbeit | PUB-ID: 2776749 OA
ter Horst, H., 2015. Ranking of disease gene associations from large corpora of scientific publications, Bielefeld: Bielefeld University.
PUB | PDF
 

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13 Publikationen

Alle markieren

[13]
2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2942743
ter Horst, H., et al., 2020. Learning soft domain constraints in a factor graph model for template-based information extraction. DATA & KNOWLEDGE ENGINEERING, 125: 101764.
PUB | DOI | WoS
 
[12]
2018 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2930952 OA
ter Horst, H., Hartung, M., & Cimiano, P., 2018. Cold-Start Knowledge Base Population Using Ontology-Based Information Extraction with Conditional Random Fields. In C. d'Amato & M. Theobald, eds. Reasoning Web. Learning, Uncertainty, Streaming, and Scalability. Lecture Notes in Computer Science. no.11078 Springer, pp. 78-109.
PUB | PDF
 
[11]
2018 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2914075 OA
Schwitteck, A., ter Horst, H., & Hartung, M., 2018. What Coreference Chains Tell about Experimental Groups in (Pre-)Clinical Trials. In Proceedings of DGfS/CL Poster Session. Stuttgart.
PUB | PDF
 
[10]
2018 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2918981 OA
ter Horst, H., et al., 2018. Assessing the Impact of Single and Pairwise Slot Constraints in a Factor Graph Model for Template-based Information Extraction. In M. Silberztein, et al., eds. Proceedings of the 23rd International Conference on Natural Language & Information Systems (NLDB). Lecture Notes in Computer Science. no.10859 Cham: Springer International Publishing, pp. 179-190.
PUB | PDF | DOI
 
[9]
2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2919923 OA
Hartung, M., et al., 2018. SANTO: A Web-based Annotation Tool for Ontology-driven Slot Filling. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (System Demonstrations). Association for Computational Linguistics.
PUB | PDF | Download (ext.)
 
[8]
2017 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2910336 OA
ter Horst, H., Hartung, M., & Cimiano, P., 2017. Joint Entity Recognition and Linking in Technical Domains Using Undirected Probabilistic Graphical Models. In J. Gracia, et al., eds. Language, Data, and Knowledge (Proceedings of the 1st International LDK Conference). Lecture Notes in Artificial Intelligence. no.10318 Springer, pp. 166-180.
PUB | PDF
 
[7]
2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2913482 OA
Borowi, A., et al., 2017. Ontology-driven Visual Exploration of Preclinical Research Data in the Spinal Cord Injury Domain. In Proceedings of the SEMANTICS 2017 Poster and Demo Track. CEUR Workshop proceedings. no.2044 Aachen: RWTH.
PUB | PDF | Download (ext.)
 
[6]
2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2913603 OA
Brazda, N., et al., 2017. SCIO: An Ontology to Support the Formalization of Pre-Clinical Spinal Cord Injury Experiments. In Proceedings of the 3rd Joint Ontology Workshops (JOWO): Ontologies and Data in the Life Sciences. CEUR Workshop proceedings. no.2050 Aachen: RWTH.
PUB | PDF | Download (ext.)
 
[5]
2016 | Datenpublikation | PUB-ID: 2902978 OA
Hakimov, S., et al., 2016. Research Data - Combining Textual and Graph-based Features for Named Entity Disambiguation Using Undirected Probabilistic Graphical Models, Bielefeld University.
PUB | Dateien verfügbar | DOI
 
[4]
2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2905552 OA
Hakimov, S., et al., 2016. Combining Textual and Graph-based Features for Named Entity Disambiguation Using Undirected Probabilistic Graphical Models. In Knowledge Engineering and Knowledge Management. Lecture Notes in Computer Science. no.10024 Springer, pp. 288-302.
PUB | PDF | DOI
 
[3]
2016 | Diskussionspapier | Veröffentlicht | PUB-ID: 2914039 OA
ter Horst, H., et al., 2016. Predicting Disease-Gene Associations using Cross-Document Graph-based Features, Bielefeld: Bielefeld University.
PUB | PDF | arXiv
 
[2]
2016 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2905448
Brazda, N., et al., 2016. SCIO: The Spinal Cord Injury Ontology, a Prerequisite for Automated Data Extraction from Publications on Research in Spinal Cord Injury. In Proceedings of the 18th Spinal Research Network Meeting (ISRT 2016). London.
PUB
 
[1]
2015 | Bielefelder Masterarbeit | PUB-ID: 2776749 OA
ter Horst, H., 2015. Ranking of disease gene associations from large corpora of scientific publications, Bielefeld: Bielefeld University.
PUB | PDF
 

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Zitationsstil: harvard1

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