| 摘要: |
| 对协同过滤算法中用户相似性计算方面进行优化，在计算用户相似性的公式中添加用户兴趣偏差度作为权重，以提高相似性计算的准确性.通过实验对改进的算法进行了验证，结果表明改进的算法提高了推荐系统的准确度. |
| 关键词: 个性化推荐 协同过滤 相似性 |
| DOI：10.3969/J.ISSN.1000-5137.2018.05.015 |
| 分类号:TP391 |
| 基金项目: |
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| Research on collaborative filtering algorithm optimization |
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XIONG Boyuan, CHEN Junhua
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College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China
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| Abstract: |
| The calculation of user similarity was optimized. By adding the user interest bias as weight into the formula of the calculation of user similarity, the accuracy was highly improved. The experiment results showed that the improved algorithm could enhance the accuracy of the recommended system. |
| Key words: personalized recommendation collaborative filtering similarity |
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