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    <abstract>In order to overcome the lack of medical corpora, we have developed a WordNet for Medical Events (WME) for identifying medical terms and their sense related information using a seed list. The initial WME resource contains 1654 medical terms or concepts. In the present research, we have reported the enhancement of WME with 6415 number of medical concepts along with their conceptual features viz. Parts-of-Speech (POS), gloss, semantics, polarity, sense and affinity. Several polarity lexicons viz. SentiWordNet, SenticNet, Bing Liu’s subjectivity list and Taboda’s adjective list were introduced with WordNet synonyms and hyponyms for expansion. The semantics feature guided us to build a semantic co-reference relation based network between the related medical concepts. These features help to prepare a medical concept network for better sense relation based visualization. Finally, we evaluated with respect to Adaptive Lesk Algorithm and conducted an agreement analysis for validating the expanded WME resource.</abstract>
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%0 Conference Proceedings
%T WME: Sense, Polarity and Affinity based Concept Resource for Medical Events
%A Mondal, Anupam
%A Das, Dipankar
%A Cambria, Erik
%A Bandyopadhyay, Sivaji
%Y Fellbaum, Christiane
%Y Vossen, Piek
%Y Mititelu, Verginica Barbu
%Y Forascu, Corina
%S Proceedings of the 8th Global WordNet Conference (GWC)
%D 2016
%8 27–30 jan
%I Global Wordnet Association
%C Bucharest, Romania
%F mondal-etal-2016-wme
%X In order to overcome the lack of medical corpora, we have developed a WordNet for Medical Events (WME) for identifying medical terms and their sense related information using a seed list. The initial WME resource contains 1654 medical terms or concepts. In the present research, we have reported the enhancement of WME with 6415 number of medical concepts along with their conceptual features viz. Parts-of-Speech (POS), gloss, semantics, polarity, sense and affinity. Several polarity lexicons viz. SentiWordNet, SenticNet, Bing Liu’s subjectivity list and Taboda’s adjective list were introduced with WordNet synonyms and hyponyms for expansion. The semantics feature guided us to build a semantic co-reference relation based network between the related medical concepts. These features help to prepare a medical concept network for better sense relation based visualization. Finally, we evaluated with respect to Adaptive Lesk Algorithm and conducted an agreement analysis for validating the expanded WME resource.
%U https://aclanthology.org/2016.gwc-1.35
%P 243-248

Markdown (Informal)

[WME: Sense, Polarity and Affinity based Concept Resource for Medical Events](https://aclanthology.org/2016.gwc-1.35) (Mondal et al., GWC 2016)

• WME: Sense, Polarity and Affinity based Concept Resource for Medical Events (Mondal et al., GWC 2016)

ACL

• Anupam Mondal, Dipankar Das, Erik Cambria, and Sivaji Bandyopadhyay. 2016. WME: Sense, Polarity and Affinity based Concept Resource for Medical Events. In Proceedings of the 8th Global WordNet Conference (GWC), pages 243–248, Bucharest, Romania. Global Wordnet Association.