Conference Paper

A Hybrid Approach of Personalized Web Information Retrieval.

MNIT, Jaipur, India
DOI: 10.1109/WI-IAT.2010.270 Conference: 2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010, Toronto, Canada, August 31 - September 3, 2010, Main Conference Proceedings
Source: DBLP

ABSTRACT This paper proposes a hybrid approach of personalized Web Information Retrieval that utilizes (1) ontology for retrieval of user's context (2) user profile that is temporarily updated according to users' browsing behavior and (3) collaborative filtering for considering recommendation of similar users. Empirical analysis reveals that Precision, Recall and F-Score of most of the queries for many users are improved with using the proposed method.

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    ABSTRACT: Web services technology is widely used as a solution of information by all users. Now a days, the user rely on web for the information need but the currently available search engines though using sophisticated document indexing algorithms, quite often gives a long list of results, much of which are not always relevant to the user's requirement. Since a user has a specific goal when searching for information, personalized search may provide the results that accurately satisfy user's specific goal and intent for the search. Personalization of web search is to retrieve information according to user's interests which may be inferred from user's actions, browsed documents or past query history etc. This paper conducts a survey of how personalization (if applied) can give useful knowledge to the user. Several user personalization approaches and techniques developed for the information retrieval domain are illustrated in this paper.
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    ABSTRACT: Nowadays, everyone can effortlessly access a range of information on the World Wide Web (WWW). As information resources on the web continue to grow tremendously, it becomes progressively more difficult to meet high expectations of users and find relevant information. Although existing search engine technologies can find valuable information, however, they suffer from the problems of information overload and information mismatch. This paper presents a hybrid Web Information Retrieval approach allowing personalised search using ontology, user profile and collaborative filtering. This approach finds the context of user query with least user's involvement, using ontology. Simultaneously, this approach uses time-based automatic user profile updating with user's changing behaviour. Subsequently, this approach uses recommendations from similar users using collaborative filtering technique. The proposed method is evaluated with the FIRE 2010 dataset and manually generated dataset. Empirical analysis reveals that Precision, Recall and F-Score of most of the queries for many users are improved with proposed method.
    I. J. Knowledge and Web Intelligence. 01/2011; 2:119-137.

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