计算机与数字工程2017，Vol.45Issue(2)：206-209,298,5.DOI:10.3969/j.issn.1672-9722.2017.02.003
基于属性值差异度的推荐多样性改进算法
An Improved Algorithm for Recommendation Diversity Based on the Dissimilarity of Attribute Value
摘要
Abstract
Recommendation diversity is increasingly becoming an important indicator to evaluate the performance of the recommendation system.There is little consideration of the dissimilarity of the item attribute value for the existing methods of improving the recommendation diversity.In this paper, an improved algorithm for recommendation diversity based on the dissimilarity of attribute value is proposed.Firstly, the dissimilarity of attribute value and item is measured.Secondly, items are clustered according to the item dissimilarity.Finally, combined with clustering information, the initial Top-N recommendation list generated by the existing recommendation algorithm is optimized.Experimental results show that the proposed algorithm can effectively improve the recommendation diversity while maintaining an acceptable level of recommendation accuracy.关键词
推荐系统/差异度/多样性/Top-N推荐/聚类Key words
recommendation system/dissimilarity/diversity/Top-N recommendation/clustering分类
信息技术与安全科学引用本文复制引用
张骏,丁艳辉,金连旭..基于属性值差异度的推荐多样性改进算法[J].计算机与数字工程,2017,45(2):206-209,298,5.基金项目
国家自然科学基金青年项目(编号:61303007) （编号:61303007）
山东省优秀中青年科学家科研奖励基金(编号:BS2013DX044)资助. （编号:BS2013DX044）
