A Study on Ontology Based Collaborative Filtering Recommendation Algorithms in E-Commerce Applications

Abstract

Recommender system is a growing proliferation in today online applications contributed to the problems of Information overloading. In a day to day life enormous amount of data is generated and collected leads to a problem of information overloading. This paper focuses on how to deal with the problem of information overloading and how to recommend an additional product to the end user using collaborative filtering (CF) recommendation algorithms. The personalized recommendation algorithm with their benefits and limitations are described. A pitfall occurs in CF recommendation system is described. An outline framework is proposed for the initial stage of recommendation. A sample problem statement is framed to show how recommendation technology is embedded in to the framework.