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混合推荐技术在Web挖掘中的研究
引用本文:王景波,郑丽英. 混合推荐技术在Web挖掘中的研究[J]. 科技信息, 2010, 0(33): I0074-I0075
作者姓名:王景波  郑丽英
作者单位:兰州交通大学电子与信息工程学院,甘肃兰州730070
摘    要:协同过滤算法是至今最成功的个性化推荐技术之一,被应用到很多领域中。但传统协同过滤算法不能及时反映用户的兴趣变化以及类似特征用户对用户相似度的精度具有影响等因素,针对这个问题,提出了一种混合推荐技术。实验表明,推荐系统的推荐质量得到显著提高。

关 键 词:推荐系统  内容过滤  协同过滤  混合推荐

Mixed Recommended Research in Web Data Mining
WANG Jing-bo,ZHENG Li-ying. Mixed Recommended Research in Web Data Mining[J]. Science, 2010, 0(33): I0074-I0075
Authors:WANG Jing-bo  ZHENG Li-ying
Affiliation:(School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou Gansu, 730070)
Abstract:Collaborative filtering is one of the most successful technologies for building recommender systems, and has been excessively used in many places. However, traditional collaborative filtering algorithms can not reflect the change of users' interest and the problems of drifting users' interests and users' feature which often results in poor recommendation, To solve this problem, this paper revises the technology of hybrid recommendation, the results of experiment have shown that the quality of the recommendation system have a extensively progress.
Keywords:Recommendation system  Content-based filtering  Collaborative filtering  Hybrid recommendation
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