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LRD: latent relation discovery for vector space expansion and information retrieval.

Gon�alves, Alexandre; Zhu, Jianhan; Song, Dawei; Uren, Victoria; Pacheco, Roberto


Alexandre Gon�alves

Jianhan Zhu

Dawei Song

Victoria Uren

Roberto Pacheco


Jeffrey Xu Yu

Masaru Kitsuregawa

Hong Va Leong


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 be-tween 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.


GONCALVES, A., ZHU, J., SONG, D., UREN, V. and PACHECO, R. 2006. LRD: latent relation discovery for vector space expansion and information retrieval. In Yu, J.X., Kitsuregawa, M. and Leong, H.V. (eds.) Advances in web-age information management: proceedings of the 7th International conference on web-age information management (WAIM 2006), 17-19 June 2006, Hong Kong, China. Lecture notes in computer science, 4016. Berlin: Springer [online], pages 122-133. Available from:

Conference Name 7th International conference on web-age information management (WAIM 2006)
Conference Location Hong Kong, China
Start Date Jun 17, 2006
End Date Jun 19, 2006
Acceptance Date Dec 31, 2006
Online Publication Date Dec 31, 2006
Publication Date Dec 31, 2006
Deposit Date May 29, 2009
Publicly Available Date May 29, 2009
Publisher Springer
Pages 122-133
Series Title Lecture notes in computer science
Series Number 4016
ISBN 3540352252; 9783540352259
Keywords Latent relation discovery; Information retrieval
Public URL


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