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LRD: Latent Relation Discovery for Vector Space Expansion and Information Retrieval

  • Alexandre Gonçalves
  • Jianhan Zhu
  • Dawei Song
  • Victoria Uren
  • Roberto Pacheco
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4016)

Abstract

In this paper, we propose a text mining method called LRD (latent relation discovery), which extends the traditional vector space model of document representation in order to improve information retrieval (IR) on documents and document clustering. Our LRD method extracts terms and entities, such as person, organization, or project names, and discovers relationships between them by taking into account their co-occurrence in textual corpora. Given a target entity, LRD discovers other entities closely related to the target effectively and efficiently. With respect to such relatedness, a measure of relation strength between entities is defined. LRD uses relation strength to enhance the vector space model, and uses the enhanced vector space model for query based IR on documents and clustering documents in order to discover complex relationships among terms and entities. Our experiments on a standard dataset for query based IR shows that our LRD method performed significantly better than traditional vector space model and other five standard statistical methods for vector expansion.

Keywords

Mutual Information Information Retrieval Relation Strength Vector Space Model Textual Corpus 
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

  • Alexandre Gonçalves
    • 1
  • Jianhan Zhu
    • 2
  • Dawei Song
    • 2
  • Victoria Uren
    • 2
  • Roberto Pacheco
    • 1
    • 3
  1. 1.Stela InstituteFlorianópolisBrazil
  2. 2.Knowledge Media InstituteThe Open UniversityMilton KeynesUnited Kingdom
  3. 3.Department of Computing and StatisticsFederal University of Santa CatarinaFlorianópolisBrazil

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