CONTENT BASED RE-RANKING OF WEB DOCUMENTS USING THE CLUSTERING AND CLASSIFICATION TECHNIQUES

Abstract

We are living in modern age, in today’s world we have vast amount of data. In order retrieve the meaningful data (information) and to knowledge discovery we perform various operations. In this internet era search engines plays a key role in information retrieval and organize the relevant data for various purposes. But the data return by a search engines is still debatable because search engines gives us our required data for a user query but also return irrelevant and redundant results. Web content mining and information retrieval is an ample and powerful research area in which retrieval of relevant information from the web resources in a faster and better manner. Web content mining improves the searching process and provides relevant information by eliminating the redundant and irrelevant contents. here unlike the page ranking algorithms we are using weighted (content) based ranking algorithm and comparing the results . further we are also using clustering technique and classification for better results . results shows this way the ranking of web documents or pages gives better performance in terms of precision recall and f-measure.