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Hybrid Approach for Query Expansion using Query Log

Lynette Lopes, Jayant Gadge Published in Information Sciences

Hybrid Approach for Query Expansion using Query Log
International Journal of Applied Information Systems
Year of Publication: 2014
© 2013 by IJAIS Journal
Series Volume 7 Number 6
Authors Lynette Lopes, Jayant Gadge
10.5120/ijais14-451204
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  1. Lynette Lopes and Jayant Gadge. Article: Hybrid Approach for Query Expansion using Query Log. International Journal of Applied Information Systems 7(6):30-35, July 2014. BibTeX

    @article{key:article,
	author = "Lynette Lopes and Jayant Gadge",
	title = "Article: Hybrid Approach for Query Expansion using Query Log",
	journal = "International Journal of Applied Information Systems",
	year = 2014,
	volume = 7,
	number = 6,
	pages = "30-35",
	month = "July",
	note = "Published by Foundation of Computer Science, New York, USA"
}

Abstract

Web search users usually submit short and ambiguous queries to specify their requirement. In order to improve performance of short and ambiguous queries, query expansion is used. Query expansion is as an effective way to improve the performance of information retrieval systems by adding relevant terms to the original query. After using search engine lots of data get accumulated, from which queries that have been used to retrieve documents are used. This data is stored as query log. These query logs provide valuable information to extract relationships between queries and documents that can be used in query expansion. This paper proposes method first to determine ambiguous queries using Kullback leibler distance model. It measures difference between two probability distributions. Second, relevant or most suitable expansion terms are selected from the documents with the analysis of relation between queries and documents. The relation can be evaluated by calculating frequency co-efficient with respect to document and document collection.

Reference

  1. Hang Cui, Ji-Rong Wen,Jian-Yun Nie and Wei-Ying Ma, "Probabilistic Query Expansion Using Query Logs"
  2. Yogesh Kakde, "A Survey of Query Expansion until June 2012", Indian Institute of Technology, Bombay, 25th June 2012.
  3. Maarten van der, Heijden Max Hinne, Wessel Kraaij, "Using query logs and click data to create improved document descriptions"
  4. Zhu Kunpeng, Wang Xiaolong, Liu Yuanchao, "A new query expansion method based on query logs" Mining
  5. School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
  6. Hazra Imran and Aditi Sharan, "Thesaurus and Query Expansion", IJCSIT, 2009
  7. Hang Cui, Ji-Rong Wen, Jian-Yun Nie and Wei-Ying Ma, "Query Expansion by Mining User Logs", IEEE transactions on knowledge and data engineering, vol. 15, no. 4, July/August 2003.
  8. Ziv BarYossef and Maxim Gurevich, "Mining Search Engine Query Logs via Suggestion Sampling".
  9. Burcu Yurekli, Gokhan Capan, Baris Yilmazel and Ozgur Yilmazel, "Guided Navigation Using Query Log Mining through Query Expansion".
  10. Rongmei Li, "Improving Web Page Retrieval using Search Context from Clicked Domain Names", 20th International workshop on database and expert system application, 2009.
  11. Ketan Singh, "Study of Different Query Expansion Techniques", Department of Computer Science and Engineering Indian Institute of Technology, Guwahati, April 2011.
  12. Dippasree Pal, Mandar Mitra, "Query Expansion Using Term Distribution and Term Association", Indian Statistical Institute, Kolkata, April 2013.

Keywords

Search engine, information retrieval, query log, ambiguity, expansion terms, co-occurrence, and suitability.