Summary of the paper

Title Concept-based Selectional Preferences and Distributional Representations from Wikipedia Articles
Authors Alex Judea, Vivi Nastase and Michael Strube
Abstract This paper describes the derivation of distributional semantic representations for open class words relative to a concept inventory, and of concepts relative to open class words through grammatical relations extracted from Wikipedia articles. The concept inventory comes from WikiNet, a large-scale concept network derived from Wikipedia. The distinctive feature of these representations are their relation to a concept network, through which we can compute selectional preferences of open-class words relative to general concepts. The resource thus derived provides a meaning representation that complements the relational representation captured in the concept network. It covers English open-class words, but the concept base is language independent. The resource can be extended to other languages, with the use of language specific dependency parsers. Good results in metonymy resolution show the resource's potential use for NLP applications.
Topics Semantics, Language modelling, Knowledge Discovery/Representation
Full paper Concept-based Selectional Preferences and Distributional Representations from Wikipedia Articles
Bibtex @InProceedings{JUDEA12.341,
  author = {Alex Judea and Vivi Nastase and Michael Strube},
  title = {Concept-based Selectional Preferences and Distributional Representations from Wikipedia Articles},
  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
  year = {2012},
  month = {may},
  date = {23-25},
  address = {Istanbul, Turkey},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-7-7},
  language = {english}
 }
Powered by ELDA © 2012 ELDA/ELRA