Type

Conference Proceedings

Authors

Seamus Lawless
Vincent Patrick Wade
Dong Zhou

Subjects

Computer Science

Topics
retrieval explicit knowledge global ranking space construction computer science information retrieval

Dual-Space Re-ranking Model for Document Retrieval (2010)

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.
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Full list of authors on original publication

Seamus Lawless, Vincent Patrick Wade, Dong Zhou

Experts in our system

1
Seamus Lawless
Trinity College Dublin
Total Publications: 71
 
2
Vincent Patrick Wade
Trinity College Dublin
Total Publications: 140