The University of Dublin | Trinity College -- Ollscoil Átha Cliath | Coláiste na Tríonóide
Trinity's Access to Research Archive
Home :: Log In :: Submit :: Alerts ::

TARA >
School of Computer Science and Statistics >
Computer Science >
Computer Science (Scholarly Publications) >

Please use this identifier to cite or link to this item: http://hdl.handle.net/2262/62178

Title: Dual-Space Re-ranking Model for Document Retrieval
Other Titles: In the Proceedings of the 23rd International Conference on Computational Linguistics, COLING 2010
Author: ZHOU, DONG
WADE, VINCENT PATRICK
LAWLESS, SEAMUS
Author's Homepage: http://people.tcd.ie/selawles
http://people.tcd.ie/zhoud
http://people.tcd.ie/vwade
Keywords: Computer Science
Issue Date: 13-Feb-2012
Abstract: The field of information retrieval still strives to develop models which allow semantic information to be integrated in the ranking process to improve perform- ance in comparison to standard bag-of- words based models. A conceptual model has been adopted in general- purpose retrieval which can comprise a range of concepts, including linguistic terms, latent concepts and explicit knowledge concepts. One of the draw- backs of this model is that the computa- tional cost is significant and often in- tractable in modern test collections. Therefore, approaches utilising concept- based models for re-ranking initial re- trieval results have attracted a consider- able amount of study. This method en- joys the benefits of reduced document corpora for semantic space construction and improved ranking results. However, fitting such a model to a smaller collec- tion is less meaningful than fitting it into the whole corpus. This paper proposes a dual-space model which incorporates external knowledge to enhance the space produced by the latent concept method. This model is intended to produce global consistency across the semantic space: similar entries are likely to have the same re-ranking scores with respect to the latent and manifest concepts. To illustrate the effectiveness of the pro- posed method, experiments were con- ducted using test collections across dif- ferent languages. The results demon- strate that the method can comfortably achieve improvements in retrieval per- formance.
Description: PUBLISHED
URI: http://hdl.handle.net/2262/62178
Related links: http://www.aclweb.org/anthology/C/C10/C10-2174.pdf
http://www.scss.tcd.ie/seamus.lawless/papers/Coling2010.pdf
Appears in Collections:Computer Science (Scholarly Publications)

Files in This Item:

File Description SizeFormat
Coling2010.pdfPublished (author's copy) - Peer Reviewed812.55 kBAdobe PDFView/Open


This item is protected by original copyright


Please note: There is a known bug in some browsers that causes an error when a user tries to view large pdf file within the browser window. If you receive the message "The file is damaged and could not be repaired", please try one of the solutions linked below based on the browser you are using.

Items in TARA are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback