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Reseach Article

A Survey on Query Recommendation Techniques and Evaluation of Snippet based Query Recommendation

Published on December 2014 by Megha R. Sisode, Ujwala M. Patil
National Conference on Emerging Trends in Information Technology
Foundation of Computer Science USA
NCETIT - Number 1
December 2014
Authors: Megha R. Sisode, Ujwala M. Patil
28694e0e-9573-41fa-b8c6-2e6a85a0f4f1

Megha R. Sisode, Ujwala M. Patil . A Survey on Query Recommendation Techniques and Evaluation of Snippet based Query Recommendation. National Conference on Emerging Trends in Information Technology. NCETIT, 1 (December 2014), 1-5.

@article{
author = { Megha R. Sisode, Ujwala M. Patil },
title = { A Survey on Query Recommendation Techniques and Evaluation of Snippet based Query Recommendation },
journal = { National Conference on Emerging Trends in Information Technology },
issue_date = { December 2014 },
volume = { NCETIT },
number = { 1 },
month = { December },
year = { 2014 },
issn = 0975-8887,
pages = { 1-5 },
numpages = 5,
url = { /proceedings/ncetit/number1/19065-3002/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Emerging Trends in Information Technology
%A Megha R. Sisode
%A Ujwala M. Patil
%T A Survey on Query Recommendation Techniques and Evaluation of Snippet based Query Recommendation
%J National Conference on Emerging Trends in Information Technology
%@ 0975-8887
%V NCETIT
%N 1
%P 1-5
%D 2014
%I International Journal of Computer Applications
Abstract

Recently web has been widely used for getting different kinds of information. Web mining is considered to store the information in a specific format known as weblog. This valuable mined information can be used in many applications such as query log analysis, query recommendation, query reformulation and many more for improved performance of search engine. Search engine provide the platform for users to describe their information need more clearly by using query recommendation. Previously there has been lot of work done for retrieving more relevant data to users in order to meet their information need thus improving performance of search engines. This paper reviews and compares different available methods in query log processing for information retrieval. Moreover the approach based on clicked snippets is better to understand users interaction process with search engines to find the appropriate information need.

References
  1. J. Wen,J. Nie, and H. Zhang. 2001. Clustering user queries of a search engine. In Proceedings of the 10th international World Wide Web conference. W3C. pp. 162– 168.
  2. O. Zaiane and A. Strilets. 2002. Finding similar queries to satisfy searches based on query traces. In Proceedings of the International Workshop on Efficient Web-Based Information Systems (EWIS), Montpellier, France.
  3. D. Broccolo, O. Frieder, F. Nardini, R. Perego and F. Silvestri. 2010. Incremental Algorithms for Effective and Efficient Query Recommendation. SPIRE 2010, LNCS 6393. pp. 13-24. Springer-Verlag Berlin Heidelberg.
  4. R. Baeza-Yates, C. Hurtado and M. Mendoza. 2004. Query Recommendation Using Query Logs in Search Engines. LNCS 3268. pp. 588-596. Springer-Verlag Berlin Heidelberg.
  5. S. Cucerzan and R. White. 2007. Query suggestion based on user landing pages. In Proceedings of SIGIR 2007. Amsterdam, Netherland.
  6. Shen Xiaoyan, Cheng Bo, Chen Junliang and Meng Xiangwu. 2008. An Effective Method for Chinese Related Queries Recommendation. In Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2008. SNPD '08. 6-8 Aug. 2008. pp. 381 - 386.
  7. He, Qi, Daxin Jiang, Zhen Liao, S. Hoi, Kuiyu Chang, Ee-Peng Lim, and Hang Li. 2009. Web query recommendation via sequential query prediction. IEEE 25th International Conference on Data Engineering, 2009. ICDE'09, IEEE, 2009. pp. 1443-1454.
  8. Zahera, H. , G. El Hady, and W. El-Wahed. 2010. Query Recommendation for Improving Search Engine Results. World Congress on Engineering and Computer Science (WCECS), San Francisco, USA. Vol. 1. 2010.
  9. Sumathi, C. P. , R. Padmaja Valli, and T. Santhanam. 2010. Automatic recommendation of web pages in web usage mining. International Journal on Computer science and Engineering (IJCSE). Vol 2 (2010): 3046-3052.
  10. Goyal, Poonam, and N. Mehala. 2011. Concept based query recommendation. Proceedings of the Ninth Australasian Data Mining Conference-Volume 121. Australian Computer Society. Inc.
  11. R. Bhushan and R. Nath. 2012. Recommendation of optimized web pages to users using Web Log mining techniques. Advance Computing Conference (IACC), 2013 IEEE 3rd International. IEEE, 2012.
  12. Y. Liu, Junwei Miao, Min Zhang, Shaoping Ma, and Liyun Ru. 2011. How do users describe their information need: Query recommendation based on snippet click model. Expert Systems with Applications 38, no. 11 (2011): 13847-13856.
Index Terms

Computer Science
Information Sciences

Keywords

Web Mining Recommendations Knowledge Extraction Query Log Processing User Behaviour Analysis Query Intent Identification Search Engines.