Personalization In Meta Searching Engine Based On Ontology

With the explosion of data on networks, it has been one of the important issues in web search application that how to efficiently get web resources to the user's mind. The acquisition of the exact web resources requires the seaching engine to display the most interesting information according to the user's preference.Therefore it provide personalized searching services for the user. Howerver, current searching engine can not meet the user's need in this respect.In this paper, we describe a new way of generating, updating and handling dynamic user profiles for personalization in web resource search. The seaching server uses a learning content-based Web Search Results classification way to cluster the search results into several classes which are characterized by distinct and comprehensive names. Then it displays the search results in the form of a tree. The server records the user's historical behaviors automatically to enrich his(her) dynamic profile without user's manual feedback,which is described by a RDF file. Such user characterizations are then used to find user groups based on optimizing and clustering those RDF files. In searching cours, We can then use the dynamic profile and the traits of the corresponding user group in web resources search to provide better services for the user.Finally, in order to improve the efficency of the searching engine, we import the conception of meta searching engine and design a model combining the personalizing idea. In addition, we practise the personalization in a semantic web researching system.