Use of hybrid of Fuzzy set and ACO for effective personalized web search

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Published: Jun 22, 2017
DOI: https://doi.org/10.26483/ijarcs.v8i5.3581
Keywords:
Fuzzy set, Information Retrieval, Ant Colony Optimization, Personalized Web Search, Search Engines, Pheromone.

Main Article Content

Suruchi Chawla
Assistant Professor

Abstract

Personalized web search techniques have been applied with success for effective information retrieval. The users search queries are vague and imprecise due to limited vocabulary of users and therefore the precision of search results is low. Fuzzy set has been used in research to infer the user’s information need from imprecise and vague queries. Ant Colony Optimization techniques(ACO) have been applied to optimize the search results in order to increase the relevant documents and improve the precision of search results. In this paper hybrid of Fuzzy set and ant colony optimization technique have been used together and an algorithm is proposed for recommendation of relevant web pages according to user’s information need. Experiment was conducted on the data set captured in three domains Academics, Entertainment, Sports and results confirm the improvement of precision of search results.

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Vol. 8 No. 5 (2017): May-June 2017
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Author Biography

Suruchi Chawla, Assistant Professor

Suruchi Chawla holds a PhD (Computer Science) from Delhi University, an MTech (Computer Science) from Kurukshetra University, and BE (Hons) in Computer Science. She is working as an Assistant Professor in the Department of Computer Science, Shaheed Rajguru College of Applied Science for Women, University of Delhi. She has over 11 years of teaching experience.

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