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


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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    • "MAR=0.8[6] MAF=0.63[6] Web Search Personalization Based on Browsing History by Artificial Immune System [WSPBHAIS] Vector WordNet X X Relevance 0.75[10] Evaluating the Effectiveness of Personalized Web Search [EEPWS] Vector X X X 0.89 [11] 0.22 [11] Improving Web Search by Categorization, Clustering, and Personalization [IWSCCP] Vector ODP X X 0.53 [12] 0.57 [12] Architecture of personalized web search engine Using suffix tree clustering [APWSSTC] X X X X 0.66 [28] 0.62 [28] A Novel Page Ranking algorithm for Personalize Web Search [ANPRPWS] Vector WordNet X X 8-18 [4] 0.5 [4] Query Expansion Based on a Personalized Web Search Model [QEPWSM] Vector User defined category X 0.80 [13] "

    EEE ICECCT 2015,; 03/2015
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    • "The study of the web information retrieval have generally been done on the repository system which organize of centralized resources, such as personalization of preferences and navigation behavior in [2], personalization of browsing behavior and collaborative filtering in [3], and the use of world knowledge base in [4]. However, resource organizers that are personal and local as in [5] have not been exploited further. "
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    ABSTRACT: This paper proposes a tracking mechanism to obtain the information sources that are stored on the personal knowledge organization which will be used to direct the search of information on the Internet by a software agent. Semantic representation of the organizer is viewed as a map of the information sources that are classified hierarchically based on the scopes of knowledge domains from the standpoint of the agent. The tracking mechanism by query will look for the information sources in the knowledge domains based on the same scope of a defined knowledge domain. This tracking will produce a list of information sources that will be followed to get the domain location as internet access preferences
    ICITACEE 2014, Semarang; 11/2014
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    ABSTRACT: The rapid expansion of the Internet has caused information overload to such an extent that the process of finding a specific piece of information may often become frustrating and time-consuming for users. In this paper, we present a hybrid personalized search model based on learning ontological user profiles implicitly. The main goal of this paper is to capture interesting and uninteresting web pages from user browsing behaviour. These web pages are stored in user profile under positive and negative documents. We propose a hybrid re- ranking algorithm that is based on the combination of different information resources collected from the reference ontology, user profile and original search engine's ranking. Experiments show that our model offers improved performance over the Google search engine.
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