Summary of the paper

Title Modelling Word Similarity: an Evaluation of Automatic Synonymy Extraction Algorithms.
Authors Kris Heylen, Yves Peirsman, Dirk Geeraerts and Dirk Speelman
Abstract Vector-based models of lexical semantics retrieve semantically related words automatically from large corpora by exploiting the property that words with a similar meaning tend to occur in similar contexts. Despite their increasing popularity, it is unclear which kind of semantic similarity they actually capture and for which kind of words. In this paper, we use three vector-based models to retrieve semantically related words for a set of Dutch nouns and we analyse whether three linguistic properties of the nouns influence the results. In particular, we compare results from a dependency-based model with those from a 1st and 2nd order bag-of-words model and we examine the effect of the nouns’ frequency, semantic speficity and semantic class. We find that all three models find more synonyms for high-frequency nouns and those belonging to abstract semantic classses. Semantic specificty does not have a clear influence.
Language Language-independent
Topics Semantics, Ontologies, Lexicon, lexical database
Full paper Modelling Word Similarity: an Evaluation of Automatic Synonymy Extraction Algorithms.
Slides Modelling Word Similarity: an Evaluation of Automatic Synonymy Extraction Algorithms.
Bibtex @InProceedings{HEYLEN08.818,
  author = {Kris Heylen, Yves Peirsman, Dirk Geeraerts and Dirk Speelman},
  title = {Modelling Word Similarity: an Evaluation of Automatic Synonymy Extraction Algorithms.},
  booktitle = {Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)},
  year = {2008},
  month = {may},
  date = {28-30},
  address = {Marrakech, Morocco},
  editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-4-0},
  note = {http://www.lrec-conf.org/proceedings/lrec2008/},
  language = {english}
  }

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