DIVERSITY IMPROVEMENT IN RECOMMENDER SYSTEM
Journal Title: International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) - Year 2013, Vol 2, Issue 2
Abstract
Recommender Systems are software tools and techniques for providing suggestions to a user. The suggestions relate to decision-making processes, like what items to buy, what music to listen to, or what online news to read. There are different ways in which recommendations can be made. The success of recommender system depends on the usefulness of the system. The usefulness can be measured in terms of accuracy, diversity, flexibility, serendipity and reliability. Most of the previous works have been focused only on improving recommendation accuracy. One of the important aspects like diversity has been never considered. In this paper several recommendation techniques have been explored. A graph based approach for maximizing diversity and item bundles for increasing capability have been proposed.
Authors and Affiliations
Antony Taurshia. A , S. Deepa Kanmani
Keywords
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