Summary of the paper

Title Discovering Fuzzy Synsets from the Redundancy in Different Lexical-Semantic Resources
Authors Hugo Gonçalo Oliveira and Fábio Santos
Abstract Although represented as such in wordnets, word senses are not discrete. To handle word senses as fuzzy objects, we exploit the graph structure of synonymy pairs acquired from different sources to discover synsets where words have different membership degrees that reflect confidence. Following this approach, a wide-coverage fuzzy thesaurus was discovered from a synonymy network compiled from seven Portuguese lexical-semantic resources. Based on a crowdsourcing evaluation, we can say that the quality of the obtained synsets is far from perfect but, as expected in a confidence measure, it increases significantly for higher cut-points on the membership and, at a certain point, reaches 100% correction rate.
Topics Lexicon, Lexical Database, Word Sense Disambiguation, Knowledge Discovery/Representation
Full paper Discovering Fuzzy Synsets from the Redundancy in Different Lexical-Semantic Resources
Bibtex @InProceedings{GONALOOLIVEIRA16.138,
  author = {Hugo Gonçalo Oliveira and Fábio Santos},
  title = {Discovering Fuzzy Synsets from the Redundancy in Different Lexical-Semantic Resources},
  booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
  year = {2016},
  month = {may},
  date = {23-28},
  location = {Portoro┼ż, Slovenia},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Sara Goggi and Marko Grobelnik and Bente Maegaard and Joseph Mariani and Helene Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  address = {Paris, France},
  isbn = {978-2-9517408-9-1},
  language = {english}
 }
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