Static Clustering of Web pages for Relevant Recommendation

Abstract: Today the Web is the large repository of information. The existence of a profusion of information, in combination with the continuously updating the web information, make its retrieval a difficult process for the user. The search activity carried out by the user is sometimes not productive according to his query. The concept of understanding the query of the user and the system varies. This intern gives rise to the results which are irrelevant for the user. The web pages in the results which are retrieved may sometimes not be according to the domain specific meaning. This leads to occupying more time of the user in searching the required web page. By clustering the web pages according to the domain will give better search results for the requested query. This paper discusses the recommendation of web pages and clustering it statically, to check the efficiency of the end result.

Keywords: Semantic Web, Domain Knowledge, Recommendation, Clustering.