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Concept-based interactive query expansion
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Source Conference on Information and Knowledge Management archive
Proceedings of the 14th ACM international conference on Information and knowledge management table of contents
Bremen, Germany
SESSION: Paper session IR-10 (information retrieval): query expansion table of contents
Pages: 696 - 703  
Year of Publication: 2005
ISBN:1-59593-140-6
Authors
Bruno M. Fonseca  Federal University of Minas Gerais: Belo Horizonte-MG, Brazil & Google Brazil, Belo Horizonte-MG, Brazil
Paulo Golgher  Google Brazil, Belo Horizonte-MG, Brazil
Bruno Pôssas  Federal University of Minas Gerais: Belo Horizonte-MG, Brazil & Google Brazil, Belo Horizonte-MG, Brazil
Berthier Ribeiro-Neto  Federal University of Minas Gerais: Belo Horizonte-MG, Brazil & Google Brazil, Belo Horizonte-MG, Brazil
Nivio Ziviani  Federal University of Minas Gerais: Belo Horizonte-MG, Brazil
Sponsors
ACM: Association for Computing Machinery
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 26,   Downloads (12 Months): 156,   Citation Count: 15
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ABSTRACT

Despite the recent advances in search quality, the fast increase in the size of the Web collection has introduced new challenges for Web ranking algorithms. In fact, there are still many situations in which the users are presented with imprecise or very poor results. One of the key difficulties is the fact that users usually submit very short and ambiguous queries, and they do not fully specify their information needs. That is, it is necessary to improve the query formation process if better answers are to be provided. In this work we propose a novel concept-based query expansion technique, which allows disambiguating queries submitted to search engines. The concepts are extracted by analyzing and locating cycles in a special type of query relations graph. This is a directed graph built from query relations mined using association rules. The concepts related to the current query are then shown to the user who selects the one concept that he interprets is most related to his query. This concept is used to expand the original query and the expanded query is processed instead. Using a Web test collection, we show that our approach leads to gains in average precision figures of roughly 32%. Further, if the user also provides information on the type of relation between his query and the selected concept, the gains in average precision go up to roughly 52%.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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B. Billerbeck, F. Scholer, H. E. Williams, and J. Zobel. Query expansion using associated queries. pages 2--9, New Orleans, USA, 2003.
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B. M. Fonseca, P. B. Golgher, E. S. de Moura, B. Pôssas, and N. Ziviani. Discovering search engine related queries using association rules. Journal of Web Engineering, 2(4):215--227, 2004.
 
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A. Geyer-Schulz and M. Hahsler. Evaluation of recommender algorithms for an internet information broker based on simple association rules and on the repeat-buying theory. In B. Masand, M. Spiliopoulou, J. Srivastava, and O. R. Zaiane, editors, Proceedings of Fourth WebKDD Workshop: Web Mining for Usage Patterns & User Profiles, pages 100--114, Edmonton, Canada, July 2002.
 
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CITED BY  15

Collaborative Colleagues:
Bruno M. Fonseca: colleagues
Paulo Golgher: colleagues
Bruno Pôssas: colleagues
Berthier Ribeiro-Neto: colleagues
Nivio Ziviani: colleagues