Diversity in Recommender Systems: A Closer Look

Abstract

Recommender Systems are widely used in numerous areas where there is enormous data. It helps to analyse such vague information and present to the end user in a simplified form. Although there are many objectives of the recommender systems like diversity, accuracy, serendipity, novelty etc., accuracy is mostly used in many cases to generate an effective system. But system will provide more desirable result by including more objectives along with accuracy. In this paper we discuss about the objective diversity and explored the existing diversity techniques and its applications in various fields.