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Reseach Article

Web Search Result Clustering using Heuristic Search and Latent Semantic Indexing

by Mansaf Alam, Kishwar Sadaf
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 44 - Number 15
Year of Publication: 2012
Authors: Mansaf Alam, Kishwar Sadaf
10.5120/6342-8633

Mansaf Alam, Kishwar Sadaf . Web Search Result Clustering using Heuristic Search and Latent Semantic Indexing. International Journal of Computer Applications. 44, 15 ( April 2012), 28-33. DOI=10.5120/6342-8633

@article{ 10.5120/6342-8633,
author = { Mansaf Alam, Kishwar Sadaf },
title = { Web Search Result Clustering using Heuristic Search and Latent Semantic Indexing },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 44 },
number = { 15 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 28-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume44/number15/6342-8633/ },
doi = { 10.5120/6342-8633 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:35:40.034332+05:30
%A Mansaf Alam
%A Kishwar Sadaf
%T Web Search Result Clustering using Heuristic Search and Latent Semantic Indexing
%J International Journal of Computer Applications
%@ 0975-8887
%V 44
%N 15
%P 28-33
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Giving user a simple and uncomplicated web search result representation is an active area of Information Retrieval research. Traditional search engines use the hyperlink structure of the web to retrieve documents or pages and give them in a ranked fashion to the user. In this paper, we propose a technique for grouping web search results into meaningful clusters. The proposed method performs heuristic search on the query result graph to prune undesired edges to form cluster and carries out Latent Semantic Indexing within these clusters to make them refined, meaningful, and relevant to the query.

References
  1. Cutting, D. R. , Kager, D. R, Pedersen, J. O. , and Tukey, J. W. 1992. Scatter/gather: a cluster-based approach to browsing large document collections. The 15th annual international ACM Sigir conference on Research and development in information retrieval, pp. 318-329.
  2. Carpenito, C. , Osinski, S. , Romano, G. and Weiss, D. 2009. A Survey of Web Clustering Engines. ACM Computing Surveys, Vol. 41, No. 3, Article 17.
  3. Zamir O. and Etzioni, O. 1998. Web document clustering: A feasibility demonstration. In Research and Development in Information Retrieal ,1998, pp. 46-54.
  4. Branson, S. and Greenberg, A. 2009. Clustering Web Search Results Using Suf?x Tree Methods. Stanford university.
  5. Janruang, J. and Guha, S. 2011. Semantic Suf?x Tree Clustering. First IRAST International Conference on Data Engineering and Internet Technology (DEIT).
  6. Zhan, D. and Dong, Y. 2004. Semantic, Hierarchical, Online Clustering of Web Search Results. Advanced Web Technologies and Applications 6th Asia-Pacific Web Conference, APWeb 2004, Hangzhou, China.
  7. Yao, T. and Li, J. 2006. A Token-based Online Web-Snippet Clustering Approach based on Directed Probability Graph. Second International Conference on Semantics, Knowledge and Grid.
  8. Sha, Y. and Zhang, G. 2009. Web search result clustering algorithm based on lexical graph. Journal Of Computational Information Systems,Volume: 5, Pages: 283-290.
  9. Kummamuru, K. , Lotlikar, R. , Roy, S. , Singal, K. and Krishnapuram, R. 2004. A Hierarchical Monothetic Document Clustering Algorithm for Summarization and Browsing Search Results. In Proceedings of the 13th international conference on World Wide Web.
  10. Zeng, H. , He, Q. , Chen, Z. , Ma, W. and Ma, J. 2004. Learning to Cluster Web Search Results. In Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information.
  11. Hearst, M. A. and Pedersen, J. O. 1996. Reexamining the cluster hypothesis: Scatter/gather on retrieval results. SIGIR-96th ACM International Conference on Research and Development in Information Retrieval pp. 76-84.
  12. Leouski, A. and Croft, W. B. 1996. An evaluation of techniques for clustering search results. Technical Report IR-76, University of Massachusetts, Amherst.
  13. Bekkerman, R. , Zilberstein, S. and Allan, J. 2007. Web Page Clustering using Heuristic Search in the Web Graph. Proceedings of IJCAI-07, the 20th International Joint Conference on Artificial Intelligence.
  14. Mecca, G. , Raunich, S. and Pappalardo, A. 2007. A New Algorithm for Clustering Search Result?. Journal of Data & Knowledge Engineering Volume 62 Issue 3, September.
  15. Brin, S. and Page, L. 1998. The anatomy of a large-scale hypertextual web search engine. In Proceedings of WWW7, Brisbane, Australia.
  16. Kleinberg, J. M. 1998. Authoritative sources in a hyperlinked environment. In proceedings of the 9th ACM-SIAM Symposium on Discrete Algorithms (SODA).
  17. Leuski, A. and Allan, J. 2000. Improving Interactive Retrieval by Combining Ranked Lists and Clustering. In Proceeding of RIAO, pp. 665-681.
  18. Wang, Y. and Kitsuregawa, M. 2001. Link Based Clustering of Web Search Results. In Proceedings of The Second International Conference on Web-Age Information Management (WAIM2001), Xi'An, P. R. China, Springer-Verlag LNCS. .
  19. Broder, A. , Kumar, R. , Maghoul, F. , Raghavan, P. , Rajagopalan, S. , Stata, R. , Tomkins, A. and Wiener, J. 2000. Graph structure in the web : Experiments and model. Proceedings of the Ninth Conference on World Wide Web, pp 309-320.
  20. Barabasi, A. and Albert, R. 1999. Emergence of Scaling in Random Networks. Science 286 (509).
  21. Baeza-Yates, R. , Castillo, C. and Lopez, V. 2005 Characteristics of the Web of Spain. Cybermetrics, Vol. 9, No. 1.
  22. Bradic, A. 2009. Search Result Clustering via Randomized Partitioning of Query-Induced Subgraphs. Telfor Journal, Vol. 1, No. 1.
  23. Deerwester, S. , Dumais, S. T. , Furnas, G. , Landauer, T. and Harshman, R. 1990. Indexing by Latent Semantic Analysis. Journal of the American Society for Information Science, pp. 391-407.
  24. Rosario, B. 2000. Latent Semantic Indexing: An overview. In Proceedings of Infosys, vol. 4.
  25. Berry, M. W. , Dumais, S. T. and O' Brien, G. W. 1995. Using linear algebra for Intelligent Information Retrieval. SIAM.
Index Terms

Computer Science
Information Sciences

Keywords

Web Search Clustering Heuristic Search Lsi Web Graph