Abstract: The web search engines are used to extract query specific information from this massive pool of World Wide Web. A large number of different search engines are available for the user to satisfy their needs. Every search engine uses its own specific algorithm to rank the list of web pages returned by the search engine for the users query, so that the most relevant page appears first in the list. Users think which search engine should be selected for searching corresponding data to any query topic for efficient search. For decision making on the basis of search result, users want to know whether they are significantly different or not. The internet contains vast amount of information that the search engines are able to provide search results that are based on page ranks. But the search results are not related to one particular users environment. In this project, a new system called as enhanced filter based personalized semantic search which would be able to provide results for search query that relates to a particular users environment, his area of interests, his likes and dislikes, the data the he/she might have found to be useful for him while searching for providing personalized search results. This process can be able to make applicable for each and every registered user in this application. User can give their basic information in their profile and get benefits from their each and every search. By this way the user can obtain results faster and more accurately. Once the search is complete one can bookmark the links of the search so that it is stored in ones profile so that it can be used for further reference one can also share the link to other profile by either sending the link as a mail or sharing with other users. Hence a more clear and informative search is done according to ones interest and domain.
P. Perumal, M.S. Geetha Devasena and R. Ramya, 2016. Enhanced Filter Based Personalized Semantic Search. Asian Journal of Information Technology, 15: 4844-4850.