Query expansion terms are often used to enhance original query formulations in document retrieval. Such terms are usually selected from the entire documents or from windows or passages surrounding query term occurrences. Arguably, the semantic relatedness between terms weakens with the increase in the distance separating them. In this paper we report a study that was conducted to systematically evaluate different distance functions for selecting query expansion terms. We propose a distance factor that can be effectively combined with the statistical term association measure of mutual information for selecting query expansion terms. Evaluation of the TREC collection shows that distance-weighted mutual information is more effective than mutual information alone in selecting terms for query expansion.
M. Beaulieu and S. Jones , Interactive searching and interface issues in the Okapi best match probabilistic retrieval system , Interacting With Computers10 (1998) 237-248 .
2.
J. J. Rocchio , Relevance feedback in information retrieval. In: G. Salton (ed.), The SMART Retrieval System - Experiments in Automatic Document Processing ( Prentice-Hall, Englewood Cliffs , 1971) 312-323.
3.
S. E. Robertson , S. Walker and M. Beaulieu , Okapi at TREC-7: automatic, ad hoc, filtering, VLC and interactive track . In: E. M. Voorhees and D. K. Harman (eds), Proceedings of the 7th Text REtrieval Conference (TREC-7) (NIST, Gaithersburg, MD, 1999) 253-264 .
4.
K. Spärck Jones , S. Walker and S. E. Robertson , A probabilistic model of information retrieval: development and comparative experiments, Parts 1 and 2 , Information Processing and Management36 (2000) 779-808, 809-840 .
5.
C. D. Manning and H. Schütze , Foundations of Statistical Natural Language Processing ( MIT Press, Cambridge, MA , 1999).
6.
T. Dunning , Accurate methods for the statistics of surprise and coincidence , Computational Linguistics19(1) (1993) 61-74 .
7.
F. Jelinek , Self-organized language modelling for speech recognition. In: A. Waibel and K. Lee (eds) Readings in Speech Recognition ( Morgan Kaufmann, San Mateo , 1990) 450-560.
8.
C. J. Van Rijsbergen , A theoretical basis for the use of co-occurrence data in information retrieval , Journal of Documentation33(2) (1977) 106-119 .
9.
K. Church , W. Gale , P. Hanks and D. Hindle , Using statistics in lexical analysis. In: U. Zernik (ed.), Lexical Acquisition: Using On-line Resources to Build a Lexicon ( Lawrence Erlbaum Associates, Englewood Cliffs , 1991) 115-164.
10.
D. Yarowsky , Word-sense disambiguation using statistical models of roget’s categories trained on large corpora . In: A. Zampolliet al. (eds), Proceedings of COLING-92, Nantes, 1992 (GETA/Champollion, 1992) 454-460 .
11.
T. McEnery and A. Wilson , Corpus Linguistics ( Edinburgh U.P., Edinburgh , 1996).
12.
O. Vechtomova , S. E. Robertson and S. Jones , Query expansion with long-span collocates , Information Retrieval6(2) (2003) 251-273 .
13.
K. Ishikawa , K. Satoh and A. Okumura , Query term expansion based on paragraphs of the relevant documents . In: E. M. Voorhees and D. K. Harman (eds), Proceedings of the 6th Text Retrieval Conference (TREC-6) (NIST, Gaithersburg, MD, 1997) 577-584 .
14.
D. Beeferman , A. Berger and J. Lafferty , A model of lexical attraction and repulsion . In: P. R. Cohen and W. Wahlster (eds), Proceedings of the 8th Conference of the European Chapter of the Association for Computational Linguistics, Madrid, Spain, 1997 (ACL, 1997) 373-380 .
15.
M. Hoey , Patterns of Lexis in Text ( Oxford University Press, Oxford , 1991).
16.
C. L. A. Clarke , G. V. Cormack and E. A. Tudhope , Relevance ranking for one to three term queries , Information Processing and Management36(2) (2000) 291-311 .
17.
D. Hawking and P. Thistlewaite , Proximity operators - so near and yet so far . In: D. K. Harman (ed.), Proceedings of the 4th Text Retrieval Conference (TREC-4) (Gaithersburg, MD, USA, 1995) 131-143 .
18.
D. Hawking and P. Thistlewaite , Relevance Weighting Using Distance between Term Occurrences (Unpublished manuscript, Joint Computer Science Technical Report Series, TR-CS-96-08, The Australian National University , 1996).
19.
B. Pôssas , N. Ziviani and W. Meira , Enhancing the set-based model using proximity information . In: A. H. F. Laender and A. L. Oliveira (eds), Proceedings of the 9th International Symposium on String Processing and Information Retrieval (SPIRE), Lisbon, Portugal, 2002 (Springer, 2002) 104-116 . [Lecture Notes in Computer Science #2476]
20.
Y. Rasolofo and J. Savoy , Term proximity scoring for keyword-based retrieval systems . In: F. Sebastiani (ed.), Proceedings of the 25th European Conference on Information Retrieval Research, Pisa, Italy, 2003 (Springer, Berlin, 2003), 207-218 . [Lecture Notes in Computer Science #2633]
21.
A. M. Lam-Adesina and G. J. F. Jones , Applying summarization techniques for term selection in relevance feedback . In: D. H. Kraftet al. (eds), Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, New Orleans, Louisiana, United States, 2001 (ACM, New York, 2001) 1-9 .
22.
J. Gao , J. Nie , H. He , W. Chen , and M. Zhou , Resolving query translation ambiguity using a decaying co-occurrence model and syntactic dependence relations . In: K. Jârvelinet al. (eds), Proceedings of the 25th annual international ACM SIGIR Conference on Research and Development in Information Retrieval, Tampere, Finland, 2002 (ACM, New York, 2002) 183-190 .
23.
E. M. Voorhees and D. K. Harman (eds.), Proceedings of the Eighth Text Retrieval Conference (TREC) (NIST, Gaithersburg, MD, 2000).
24.
R. Fano , Transmission of information ( MIT Press, Cambridge, MA , 1961).
25.
Y. Wang, The Use of Term Proximity in Collocate-Ranking for Query Expansion (Unpublished manuscript, Masters Thesis, Department of Management Sciences, University of Waterloo, Canada, 2004).
26.
Y. Wang and O. Vechtomova , Exploring the use of term proximity in collocate-ranking for query expansion . In: P. Liddellet al. (eds), Proceedings of the 17th Joint ACH/ALLC (Association for Computers and the Humanities/Association for Literary and Linguistic Computing) Conference, Victoria, BC, Canada, 2005 (Humanities Computing & Media Centre, University of Victoria, 2005) 257-259 .
27.
S. E. Robertson , On term selection for query expansion , Journal of Documentation46 (1990) 359-364 .
28.
J. Xu and W. B. Croft , Query expansion using local and global document analysis . In: H.-P. Freiet al. (eds), Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Zurich, Switzerland, 1996 (ACM, New York, 1996) 4-11 .
29.
T. R. Niesler and P. C. Woodland , Modeling word-pair relations in a category-based language model . In: Proceedings of the International Conference on Acoustics, Speech, and Signal, Munich, Germany, 1997 (IEEE, 1998) 795-798 .
30.
Y. Jing and W. B. Croft , An Association Thesaurus for Information Retrieval (Unpublished manuscript, Technical Report, UM-CS-1994-017, University of Massachusetts, Amherst, MA, USA , 1994).
31.
S. Evert and H. Kermes , The influence of linguistic pre-processing on candidate data . In: B. Krennet al. (eds), Proceedings of the Workshop on Computational Approaches to Collocations, Vienna, Austria, 2002. Available at: www.ofai.at/%7Ebrigitte.krenn/colloc02/ (accessed 3 April 2006).
