DocumentCode :
151465
Title :
A novel approach to personalize web search through user profiling and query reformulation
Author :
Makvana, Kamlesh ; Shah, Parikshit ; Shah, Parikshit
Author_Institution :
Inf. Technol., Charusat Univ., Changa, India
fYear :
2014
fDate :
5-6 Sept. 2014
Firstpage :
1
Lastpage :
10
Abstract :
With a inundating of information in WWW (World Wide Web) users are often failed to retrieve search result in context of their interest through existing search engines. So the personalization of web search result has to be carryout that process user´s query and re-rank retrieved results based on their interest. User have diverse background on same query, it is very difficult for some informative query to identify user´s current intention. In this paper, a novel approach is proposed that personalize web search result through query reformulation and user profiling. First, a framework is proposed that identify relevant search term for particular user from previous search history by analysing web log file maintained in the server. These terms are appended to user´s ambiguous query. Second, the proposed approach proceeds the user´s search result and re-rank the retrieved result by identifying interest value of user on retrieved links. Proposed new approach also identify user interest on retrieved links by combing the user interest value generated from VSM (Vector Space Model) and actual rank of that link. Third, the framework also suggest some keywords that help to incorporate user´s current interest. Finally, experimental result shows the effectiveness of proposed search engine with commercial search engine with different criteria.
Keywords :
Internet; query processing; search engines; vectors; VSM; WWW users; Web log file; Web search personalization; Web server; World Wide Web; ambiguous query; query reformulation; relevant search term; search engines; user interest value; user profiling; vector space model; Context; Google; History; Knowledge based systems; Search engines; Vectors; Web search; Information Retrieval; Personalized Web search; Re-Ranking Algorithm; Semantic Web Mining; User Profiling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining and Intelligent Computing (ICDMIC), 2014 International Conference on
Conference_Location :
New Delhi
Print_ISBN :
978-1-4799-4675-4
Type :
conf
DOI :
10.1109/ICDMIC.2014.6954221
Filename :
6954221
Link To Document :
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