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A New Ranking Algorithm for Ranking Search Results of Search Engine based on Personalized User Profile

International Journal of Computer Applications
© 2013 by IJCA Journal
Volume 74 - Number 15
Year of Publication: 2013
S. Geetha Rani

Geetha S Rani. Article: A New Ranking Algorithm for Ranking Search Results of Search Engine based on Personalized User Profile. International Journal of Computer Applications 74(15):7-11, July 2013. Full text available. BibTeX

	author = {S. Geetha Rani},
	title = {Article: A New Ranking Algorithm for Ranking Search Results of Search Engine based on Personalized User Profile},
	journal = {International Journal of Computer Applications},
	year = {2013},
	volume = {74},
	number = {15},
	pages = {7-11},
	month = {July},
	note = {Full text available}


The user profile is a main component in personalization applications. An accurate user profile can greatly improve a search engine's performance by identifying the information needs of individual users. The desired information can be obtained by submitting the respective query. Different query gives different information. The information which is more relevant for the given query can be analyzed and evaluated. The user profile is used to rank the documents in a search engine for a submitted query. Many user profiling strategies based on positive preferences preferences (i. e. , Objects that users are interested in). Later some user profiling strategies were based on both positive as well as negative preferences (i. e. , objects that users dislike). In Existing research only the count of a click can be evaluated. In this research, click count as well as Link-Click based Ranking Algorithm is being proposed. In this Algorithm the count of click of each query concept can be evaluated as well as the link also evaluated in the submitted query for three user profiling strategies. The relevance between the query and information obtained can be analyzed, evaluated and ranked. The goal of the proposed ranking approach is providing the user with more satisfied results to get relevant information based on Link and Click approach rather than Click count.


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