Word Sense Discrimination: A Gangplank Algorithm

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In this paper we present an unsupervised, graph-based approach for Word Sense Discrimination. Given a set of text sentences, a word co-occurrence graph is derived and a distance based on Jaccard index is defined on it; subsequently, the new distance is used to cluster the neighbour nodes of ambiguous terms using the concept of “gangplanks” as edges that separate denser regions (“islands”) in the graph. The proposed approach has been evaluated on a real data set, showing promising performance in Word Sense Discrimination.
Original languageEnglish
Title of host publicationProceedings of the second Italian conference on Computational Linguistics CLiC-it 2015
Number of pages5
Publication statusPublished - 2015
EventCLiC-it 2015 - Fondazione Bruno Kessler, Trento
Duration: 3 Dec 20154 Dec 2015


ConferenceCLiC-it 2015
CityFondazione Bruno Kessler, Trento


  • Natural Language Processing
  • Word Sense Discrimination
  • graph-based methods
  • unsupervised methods

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