Abstract:
Aiming at the common problems including difficulties in product content analysis, low density in customer scores and new customer recommendation, existing in recommendation technologies today, this paper designs a blending recommendation technology which employs demography analysis technology based on cooperating filtering technology, and implements a recommendation model instance in a Web resource system. Experimental results indicate that this technology can solve the problems mentioned before, and efficiently improve recommendation quality comparing to the traditional technologies.
Key words:
blending recommendation technology,
customer clustering,
cooperating filtering,
individualized resource recommendation
摘要:
针对当前推荐技术普遍存在的产品内容分析难度大、用户评价信息稀疏和新用户推荐等问题,基于协同过滤技术,引入人口统计信息分析技术,提出一种混合推荐技术,并在Web资源系统中实现一个推荐模型实例。实验结果表明,应用该技术不但能够解决上述问题,相较传统的推荐技术,还能有效提高推荐质量。
关键词:
混合推荐技术,
用户聚类,
协同过滤,
个性化资源推荐
CLC Number:
ZHANG Chi, CHEN Gang, WANG Hui-Min. Recommendation Model Based on Blending Recommendation Technology[J]. Computer Engineering, 2010, 36(22): 248-250.
张驰, 陈刚, 王慧敏. 基于混合推荐技术的推荐模型[J]. 计算机工程, 2010, 36(22): 248-250.