Web Personalization System for Online News

Abstract

Web personalization can be defined as the process of customizing the content and structure of a Web site to the specific and individual needs of each user taking advantages of the user’s navigational behavior. Recommender System applies knowledge of discovery technique to the problem of making personalized recommendation for information, products or services. The content-based filtering approach recommends the contents that the user likes in the past. Content-Based filter recommends items based solely on a profile built up by analyzing the content of items that a user has rated. The collaborative filtering approach recommends the contents that are liked by other users with similar interests. In this paper, an effective frame-work for combining content and collaborative filtering is used to predict news articles of interest for user. The proposed system is developed using the feature of web personalization to improve the recommend-dation process of the system.