An Approach to Effective Recommendation Considering User Preference and Diversity Simultaneously

Sang-Chul LEE  Sang-Wook KIM  Sunju PARK  Dong-Kyu CHAE  

IEICE TRANSACTIONS on Information and Systems   Vol.E101-D   No.1   pp.244-248
Publication Date: 2018/01/01
Publicized: 2017/09/28
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2017EDL8039
Type of Manuscript: LETTER
Category: Data Engineering, Web Information Systems
diversification,  e-commerce,  recommender system,  

Full Text: PDF(481.6KB)>>
Buy this Article

This paper addresses recommendation diversification. Existing diversification methods have difficulty in dealing with the tradeoff between accuracy and diversity. We point out the root of the problem in diversification methods and propose a novel method that can avoid the problem. Our method aims to find an optimal solution of the objective function that is carefully designed to consider user preference and the diversity among recommended items simultaneously. In addition, we propose an item clustering and a greedy approximation to achieve efficiency in recommendation.