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Unsupervised Labeling of Noun Clusters

  • Theresa Jickels
  • Grzegorz Kondrak
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4013)

Abstract

Semantic knowledge is important in many areas of natural language processing. We propose a new unsupervised learning algorithm to annotate groups of nouns with hypernym labels. Several variations of the algorithm are presented, including a method that utilizes semantic information from WordNet. The algorithm’s results are compared against an independently-developed labeling method. The evaluation is performed using labels assigned to noun clusters by several participants of a specially designed human study.

Keywords

Dependency Data Computational Linguistics Feature Word Label Algorithm Feature Score 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Theresa Jickels
    • 1
  • Grzegorz Kondrak
    • 1
  1. 1.Department of Computing ScienceUniversity of AlbertaEdmontonCanada

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