基于改进相似度计算的图书推荐算法

2018 3rd International Conference on Mechanical, Control and Computer Engineering (ICMCCE) Pub Date : 2018-09-01 DOI:10.1109/ICMCCE.2018.00135

Yue Li

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引用次数: 0

摘要

推荐系统可以解决海量数据中的信息过载问题，推荐用户感兴趣的内容。用户相似度计算是一种常见的推荐算法，但传统算法只考虑用户-物品评分之间的相似度，忽略了用户固有特征的影响。本文提出了一种结合用户特征相似度和用户-物品评分相似度的推荐算法，并提出使用F1指标来评价推荐算法的效率。实验结果表明，改进后的算法可以有效地提高推荐效果。

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A Book Recommendation Algorithm Based on Improved Similarity Calculation

Rcommendation system can solve the information overload in mass data and recommend content that users are interested in. User similarity calculation is a common recommendation algorithm, but the traditional algorithm only considers the similarity between user-item ratings and ignores the influence of users' inherent characteristics. This paper presents an algorithm combining user feature similarity and user-item rating similarity, and proposes to use F1 indicator to evaluate the efficiency of the recommendation algorithm. The hexperimental results show that the improved algorithm can effectively improve the recommendation effect.

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来源期刊

2018 3rd International Conference on Mechanical, Control and Computer Engineering (ICMCCE)

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