A Community-Based Recommendation System to Reveal Unexpected Interests

J. Kamahara, T. Asakawa, S. Shimojo, H. Miyahara
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引用次数: 66

Abstract

Current collaborative filtering can't represent various aspects of users' interests. We propose a recommendation method in which a user can find new interests that are partially similar to the user's taste. Partial similarity is an aspect of the user's preference which is projected by the community in which the user belongs. We developed a television program recommendation system which performs such recommendation with serendipity, conducted an actual experiment and evaluated its results.
基于社区的推荐系统揭示意外兴趣
当前的协同过滤不能代表用户兴趣的各个方面。我们提出了一种推荐方法,在这种方法中,用户可以找到与用户口味部分相似的新兴趣。部分相似是用户偏好的一个方面,它是由用户所属的社区投射出来的。我们开发了一个具有偶然性的电视节目推荐系统,进行了实际的实验并对结果进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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