| 基于Web挖掘的个性化推荐算法研究 |
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| 引用本文： | 杨艳霞 于海平 陈 燕. 基于Web挖掘的个性化推荐算法研究[J]. 计算机与数字工程, 2014, 0(4): 674-677 |
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| 作者姓名： | 杨艳霞 于海平 陈 燕 |
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| 作者单位： | 武汉科技大学城市学院信息工程学部,武汉430083 |
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| 摘 要： | 个性化推荐系统是根据用户的爱好,给用户推荐符合用户兴趣的对象的一种高级商务智能平台.论文重点探讨基于用户的协同过滤算法,介绍其基本思想和工作流程,并通过高级语言C＋＋来实现三种相似度计算方法,通过实验比较得出了最佳的计算方法,并设计实现了一个电子商务个性化推荐系统原型,对其他同类网站应用个性化推荐系统具有很好的参考价值.
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| 关 键 词： | 个性化推荐 协同过滤 相似度算法 |
Personalized Recommendation Algorithm Based on Web Data Mining |
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| YANG Yanxia,YU Haiping,CHEN Yan. Personalized Recommendation Algorithm Based on Web Data Mining[J]. Computer and Digital Engineering, 2014, 0(4): 674-677 |
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| Authors: | YANG Yanxia YU Haiping CHEN Yan |
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| Affiliation: | (Department of Information Engineering, Wuhan University of Science and Technology City College, Wuhan 430083) |
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| Abstract: | Personalized recommendation system is an advanced business intelligence platform is used based on the user＇s preference recommended to the user object that matches the user interest. The user-based collaborative filtering algorithm is focused on. Its basic idea and working process are introduced. The highqevel language C＋＋ is used to gain three different methods to calculate similarity degree. After series of experiments and comparisons the best one is obtained. Then an e-com- merce application prototype is designed and implemented, which provides a good reference for other websites to apply the Personalized Recommender System |
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| Keywords: | personalized recommendation collaborative filtering similarity algorithm |
| 本文献已被 CNKI 维普 等数据库收录！ |
