COMPARISION BETWEEN THE CONTENT BASED FILTERING AND COLLABORATIVE FILTERING TECHNIQUES

On the Internet, content filtering (also known as information filtering) is the use of a program to screen and exclude from access or availability Web pages or e-mail that is deemed objectionable. Content filtering is used by corporations as part of Internet firewall computers and also by home computer owners, especially by parents to screen the content their children have access to from a computer. Content filtering usually works by specifying character strings that, if matched, indicate undesirable content that is to be screened out. In this paper, we present the combination of the two filtering techniques including the content-based and collaborative filtering. Content-based filtering selects information based on semantic content, whereas collaborative filtering combines the opinions of other users to make a prediction for a target user. In this paper, we describe a new filtering approach that combines the content-based filter and collaborative filter to capitalize on their respective strengths, and thereby achieves a good performance .Finally, we comparing the two filtering techniques and in this two techniques find the result of which one is the best technique.