Call for Paper - May 2023 Edition
IJCA solicits original research papers for the May 2023 Edition. Last date of manuscript submission is April 20, 2023. Read More

A Hybrid Context Based Approach for Web Information Retrieval

International Journal of Computer Applications
© 2010 by IJCA Journal
Number 7 - Article 5
Year of Publication: 2010
W. Aisha Banu
Dr. P. Sheikh Abdul Kader

Aisha W Banu and Dr. Sheikh Abdul P Kader. Article:A Hybrid Context Based Approach for Web Information Retrieval. International Journal of Computer Applications 10(7):25–28, November 2010. Published By Foundation of Computer Science. BibTeX

	author = {W. Aisha Banu and Dr. P. Sheikh Abdul Kader},
	title = {Article:A Hybrid Context Based Approach for Web Information Retrieval},
	journal = {International Journal of Computer Applications},
	year = {2010},
	volume = {10},
	number = {7},
	pages = {25--28},
	month = {November},
	note = {Published By Foundation of Computer Science}


Information retrieval mechanisms from the web are a great need of the hour as the amount of the content is growing dynamically every day. There are many algorithms which have been proposed in literature mainly relying on the output of the search engines. These algorithms are either content based or snippet based and perform a clustered outcome re-ranking of the content for the user. This work proposes a hybrid approach to content clustering that combines the best of the web information retrieval methods and also uses the personal preference information of the users modeling a wide range of contexts. This work introduces a context mechanism of the users in the overall process and presents taxonomy of the methods to organize the output of the search engines. Experimental results are promising and show that this approach has great promise for a wide range of queries.


  • S. Nunes. 2007. Exploring temporal evidence in web information retrieval. BCS IRSG Symposium: Future Directions in Information Access.
  • R. Manmat`ha, T. Rath and T. Feng. 2001. Modeling score distributions for combining the outputs of search engines. In Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, New York.
  • Yu-Ting Liu, Tie-Yan Liu, Tao Qin, Zhi- Ming Ma, and Hang Li. 2007. Supervised rank aggregation. Analyzing Partially Ranked Data, In Proc. of the International World Wide Web Conference Notes in Statistics. Springer-Verlag, 1985. (WWW),
  • L Si, J Callan. 2003. A Semi supervised Learning Method to Merge Search Engine Results , ACM Transactions on Information Systems (TOIS), -
  • Alexandre Klementiev, Dan Roth, and Kevin Small. 2008. Unsupervised rank aggregation with distance-based models. In Proc. of the International Conference on Machine Learning (ICML).
  • Chen, P.-M. and Kuo, F. 2000. C. An information retrieval system based on a user profile. J. Syst. Softw., 54 (1). 3-8.
  • Mylonas, P. and Avrithis, Y., 2005. Context modeling for multimedia analysis. in Proc. of 5th International and Interdisciplinary Conference on Modeling and Using Context (CONTEXT â€TM05), (Paris, France)
  • icrosssing, How America searches Mobile, Technical Report.
  • Zamir, O., and Etzioni, O. 1998. Web document clustering: a feasibility demonstration. In SIGIR ’98: Proceedings of the 21st annual international ACM SIGIR conference on research and development in information retrieval, 46–54.New York, NY, USA: ACM