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.
- SourceAvailable from: Chetan Awati[Show abstract] [Hide abstract]
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
- [Show abstract] [Hide abstract]
ABSTRACT: This paper presents an approach to personalized web search that is based on augmenting query with additional keywords extracted from interested person's profile. The profile reflects interested person's interests, past searching experiences etc. It is represented by a set of weighted keywords displayed conveniently as a keyword cloud. Experiments on web search show that our search system can improve relevancy over popular search engines.