Ranking of Searched Documents Using Semantic Technology

World Wide Web is a vast resource of data growing continuously. Nowadays, it becomes increasingly hard for users to retrieve useful data due to the continually rapid growth in data volume. This vast amount of data is making search more and more difficult with traditional search engine as they return huge data for a given query which is consisting of relevant as well as irrelevant data. This is not only results in wastage of user time but also lead to data overload problem. So, users are not satisfied with searching the information by traditional search engine. So the problem of re-ranking search pages or results has become one of the main problems in IR field. Currently searching methods are mainly based on keyword matching technique but this technique has some weaknesses. The first weakness is that web users cannot express their search intention accurately or properly using several keywords. So most of the time, the exactly matched results do not satisfy the web users. Second weakness is that keyword matching cannot sure the selected candidates have high correlation with the user's query, given the different meanings of the keywords. Another problem about traditional search engines is their ranking methods. To fulfil the requirement of users we are using Semantic search engine with page ranking algorithm which will search the data semantically and holds the capability to re-rank search results effectively and try the best to arrange the web results which are most relevant for the users. The proposed algorithm for page ranking is based on result of semantic web with user attention time.