Agent Based Adapted Semantic Enhanced Web Information Retrieval Process Analysis

Abstract

Every user has an individual background and a precise goal in search of information. Although modern methods of information retrieval have enormously improved our ability to find relevant information for distributed environment, it remains the case for the foreseeable future that the best performance can only be obtained by some pre-processing of the documents to be searched. Web Information retrieval system assumes a noteworthy part in retrieving the information from a larger collection of data. The goal of personalized search is to search results to a particular user based on the user’s interests and preferences. Effective personalization of information access involves two important challenges: accurately identifying the user context and organizing the information to match with the particular context. In this paper, the system uses ontology as a knowledge base for the information retrieval process.  It is one layer above   any   one of search engines retrieve by analyzing just the keywords. Here, the query is analyzed both syntactically and semantically. The developed system retrieves the web results more relevant to the users query. The level of accuracy will be enhanced since the query is analyzed semantically. The results are re-ranked and optimized for providing the relevant links.  Based on the user’s information access behavior, an ontological profile is created, which is also used for personalization. If the system is deployed for web information gathering, search performance can be improved and  accurate results can be retrieved.