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Collaborative Filtering Algorithm Based Bhattacharyya Coefficient

Published in Computer Science and Application • Jan 1, 2017
NobleIDNI3P42W92R61S51
Authors:
少鑫 姜

Abstract

为了克服协同过滤算法的稀疏性问题和传统相似度计算方法过度依赖共同评分的问题,本文引入巴氏系数改进修正余弦相似度,进而提出基于巴氏系数的协同过滤算法(CFBC)。改进的算法考虑了项目全局评分信息和局部评分信息,克服了对于共同评分项的依赖。为了证明CFBC算法的有效性,我们基于已有的相似度计算方法实现了协同过滤算法,实验结果表明CFBC算法提高了推荐的准确性。 In order to solve the problems of Collaborative Filtering in terms of sparsely and the traditional similarity calculatio...

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