| Concept-based interactive query expansion |
| Full text |
Pdf
(154 KB)
|
| 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 |
|
| Publisher |
|
| Bibliometrics |
Downloads (6 Weeks): 26, Downloads (12 Months): 156, Citation Count: 15
|
|
|
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.
 |
1
|
Rakesh Agrawal , Tomasz Imieliński , Arun Swami, Mining association rules between sets of items in large databases, Proceedings of the 1993 ACM SIGMOD international conference on Management of data, p.207-216, May 25-28, 1993, Washington, D.C., United States
|
 |
2
|
|
 |
3
|
|
| |
4
|
|
| |
5
|
B. Billerbeck, F. Scholer, H. E. Williams, and J. Zobel. Query expansion using associated queries. pages 2--9, New Orleans, USA, 2003.
|
 |
6
|
|
| |
7
|
C. Buckley, G. Salton, J. Allan, and A. Singhal. Automatic query expansion using SMART: Trec-3 report. In Proceedings of the Third Text REtrieval Conference, pages 69--80, 1995.
|
 |
8
|
|
 |
9
|
Hang Cui , Ji-Rong Wen , Jian-Yun Nie , Wei-Ying Ma, Probabilistic query expansion using query logs, Proceedings of the 11th international conference on World Wide Web, May 07-11, 2002, Honolulu, Hawaii, USA
[doi> 10.1145/511446.511489]
|
 |
10
|
|
 |
11
|
|
| |
12
|
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.
|
| |
13
|
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.
|
| |
14
|
|
 |
15
|
|
| |
16
|
|
 |
17
|
|
| |
18
|
|
 |
19
|
|
CITED BY 15
|
|
|
|
|
|
|
|
|
|
|
Francesco Bonchi , Carlos Castillo , Debora Donato , Aristides Gionis, Topical query decomposition, Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, August 24-27, 2008, Las Vegas, Nevada, USA
|
|
|
|
|
|
|
|
|
Huanhuan Cao , Daxin Jiang , Jian Pei , Qi He , Zhen Liao , Enhong Chen , Hang Li, Context-aware query suggestion by mining click-through and session data, Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, August 24-27, 2008, Las Vegas, Nevada, USA
|
|
|
|
|
|
Ranieri Baraglia , Fidel Cacheda , Victor Carneiro , Vreixo Formoso , Raffaele Perego , Fabrizio Silvestri, Search shortcuts using click-through data, Proceedings of the 2009 workshop on Web Search Click Data, p.48-55, February 09-09, 2009, Barcelona, Spain
|
|
|
Huanhuan Cao , Daxin Jiang , Jian Pei , Enhong Chen , Hang Li, Towards context-aware search by learning a very large variable length hidden markov model from search logs, Proceedings of the 18th international conference on World wide web, April 20-24, 2009, Madrid, Spain
|
|
|
|
|
|
|
|
|
|
|
|
Huanhuan Cao , Derek Hao Hu , Dou Shen , Daxin Jiang , Jian-Tao Sun , Enhong Chen , Qiang Yang, Context-aware query classification, Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, July 19-23, 2009, Boston, MA, USA
|
|
|
Shu Huang , Qiankun Zhao , Prasenjit Mitra , C. Lee Giles, Hierarchical location and topic based query expansion, Proceedings of the 23rd national conference on Artificial intelligence, p.1150-1155, July 13-17, 2008, Chicago, Illinois
|
|