Query Expansion Based on a Personalized Web Search Model
ABSTRACT A novel query expansion algorithm is proposed in this paper. It is based on a model of personalized web search system. The new system, as a middleware between a user and a Web search engine, is set up on the client machine. It can learn a user's preference implicitly and then generate the user profile automatically. When the user inputs query keywords, more personalized expansion words are generated by the proposed algorithm, and then these words together with the query keywords are submitted to a popular search engine such as Baidu or Google. These expansion words can help a search engine retrieval information for a user according to his/her implicit search intentions. The new Web search model can make a common search engine personalized, that is, throughout personalized query expansion the search engine can return different search results to different users who input the same keywords. The experimental results show the effect and applicability of the presented work for personalized information service of a search engine.
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ABSTRACT: Area of mobile web search personalization is gaining demand due to relevancy of results. Generally user relevance is captured in the form of profiles. Profile generated implicitly according to user search history or explicitly using appropriate interface. We propose personalized mobile search engine that take best features of both implicit & explicit user profiles for personalization. Implicit user profile is ontology-based & multifaceted. Concepts are divided into content concepts & location concepts to understand importance of location in the personalization. GPS locations are also used for better personalization. In this paper, explicit user profiles created, deleted & edited through user interface. System evaluates relevancy of search results using Normalized Kendall Tau Distance, precision & recall. Experimental results show that effectiveness of personalization has improved.International Conference on Industrial Electronics and Computer Engineering at New Delhi, New Delhi, India; 08/2014
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ABSTRACT: The system proposes a hybrid approach to combine explicit & implicit user profiles for mobile web search personalization. User profiles are used to retrieve search results according to user relevance. Generally implicit profiles tracked by user’s clickthrough data & its GPS data are widely used for personalization purpose. Explicit user profiles created to update user interests time to time. This system will implement an application to combine benefits from both user profiles. Finally it will compare performance of system with implicit user profile results to evaluate effectiveness of proposed work.IFRSA’s International Journal of Computing, INDIA; 01/2014
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ABSTRACT: The advent of the Web has raised different searching and querying problems. Keyword matching based querying techniques used by various search engines, return thousands of Web documents for a single query, and most of these documents are generally are unrelated to the users' required information. Queries submitted to a search engine may have ambiguous meanings. For example, depending on the users , the query "apple" may refer to a fruit, the company Apple Computer and so forth. Thus, providing personalized query suggestion (e.g., users interested in "apple" as a fruit get suggestions about fruit, while users interested in "apple" as a company) will help the user in getting the desired information. This makes the current retrieval systems far from optimal. Also because of geography's important role in search requests, methods are required which aim at giving improved answers to geographic search requests. Geo search applications can use a standard keyword interface and extract geographic information (implicit or explicit) from queries, employ graphic interfaces such as interactive maps, or use the current location of a mobile user. This paper focuses on the survey of many efficient Context aware Personalized Web search approaches with geographical information which were proposed by many authors.