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Using Generalization of Syntactic Parse Trees for Taxonomy Capture on the Web

  • Boris A. Galitsky
  • Gábor Dobrocsi
  • Josep Lluis de la Rosa
  • Sergei O. Kuznetsov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6828)

Abstract

We implement a scalable mechanism to build a taxonomy of entities which improves relevance of search engine in a vertical domain. Taxonomy construction starts from the seed entities and mines the web for new entities associated with them. To form these new entities, machine learning of syntactic parse trees (syntactic generalization) is applied to form commonalities between various search results for existing entities on the web. Taxonomy and syntactic generalization is applied to relevance improvement in search and text similarity assessment in commercial setting; evaluation results show substantial contribution of both sources.

Keywords

learning taxonomy learning syntactic parse tree syntactic generalization search relevance 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Boris A. Galitsky
    • 1
  • Gábor Dobrocsi
    • 1
  • Josep Lluis de la Rosa
    • 1
  • Sergei O. Kuznetsov
    • 2
  1. 1.University of GironaGironaSpain
  2. 2.Higher School of EconomicsMoscowRussia

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