Query Expansion Using Wordnet.

Date of Submission

December 2011

Date of Award

Winter 12-12-2012

Institute Name (Publisher)

Indian Statistical Institute

Document Type

Master's Dissertation

Degree Name

Master of Technology

Subject Name

Computer Science

Department

Computer Vision and Pattern Recognition Unit (CVPR-Kolkata)

Supervisor

Mitra, Mandar (CVPR-Kolkata; ISI)

Abstract (Summary of the Work)

Query expansion is an effective technique to improve the performance of information retrieval systems. Intuitively, hand-crafted lexical resources, like WordNet, should provide reliable related terms for expanding queries. Most previous studies have shown that query expansion using only WordNet leads to very limited performance improvements. However, a recent study has shown the effectiveness of query expansion using WordNet within the recently proposed axiomatic framework. In this thesis, we re-examine the problem using the BM25 model. By defining new term weighting strategies, we are able to use the lexical information within WordNet to expand queries effectively. We obtained notable improvements while testing on the TREC7 and TREC8 collections. We observed that massive expansion leads to better performance. A tentative explanation of this observation is also explored.

Comments

ProQuest Collection ID: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:28843069

Control Number

ISI-DISS-2011-296

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

DOI

http://dspace.isical.ac.in:8080/jspui/handle/10263/6453

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