Title: Intelligent web search system for personalised web search based on recommendation of web page communities

Authors: Suruchi Chawla

Addresses: Department of Computer Science, Shaheed Rajguru College of Applied Science for Women, University of Delhi, Vasundhara Enclave, Delhi – 110096, India

Abstract: In this paper an intelligent web search system is proposed based on recommendation of web page communities for personalised web search (PWS). Web page communities are set of web pages that provide the good quality resource on a given topic. The intelligent search system adapts the web search to the user's information need based on recommendation of web page communities. The groups of similar content clicked web pages in clusters are selected for generation of web page communities using maximum flow algorithm with hyperlink-induced topic search (HITS). The cluster of web page communities is selected for recommendations of relevant web pages to user during web search for effective web information retrieval. Experiment was conducted on collection of web query sessions in academics, entertainment and sports domain. The experimental results were compared with classic IR and PWS (HITS) based on same dataset and hence the results show the improvement in precision of search results using intelligent web search based on web page communities.

Keywords: intelligent web search; search engine; information scent; clustering; web page communities; personalised web search; PWS; hubs; authorities; hyperlink-induced topic search; HITS.

DOI: 10.1504/IJISDC.2019.105793

International Journal of Intelligent Systems Design and Computing, 2019 Vol.3 No.1, pp.12 - 30

Accepted: 23 Apr 2019
Published online: 13 Mar 2020 *

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