文献类型：期刊文献

中文题名：基于集团序方法的推荐系统输出

英文题名：Output of recommender systems based on aggregative rank

作者：崔春生[1]

通讯作者：Cui, C.-S.

机构：[1]河南财经政法大学计算机与信息工程学院

第一机构：河南财经政法大学计算机与信息工程学院

年份：2013

卷号：33

期号：7

起止页码：1845-1851

中文期刊名：系统工程理论与实践

外文期刊名：Systems Engineering-Theory & Practice

收录：CSTPCD;;国家哲学社会科学学术期刊数据库;EI(收录号：20133216587991);Scopus(收录号：2-s2.0-84880996376);北大核心:【北大核心2011】；CSSCI:【CSSCI2012_2013】；CSCD:【CSCD2013_2014】；

基金：国家社会科学基金(12BTQ011);河南省软科学(132400410254);河南教育厅基础研究(12B120001)

语种：中文

中文关键词：推荐系统;个性化推荐;电子商务;集团序;推荐输出

外文关键词：recommender systems; personalization recommendation; electric commerce; aggregative rank;output functional

摘要：论文从推荐系统的输出形式出发,认为系统以top-N形式输出时,N值的大小影响了推荐的质量和推荐个性化.论文探讨了输出结果差异化的可行性及一般方法,采用集团序的方法提出以整个子集团作为推荐输出、以子集团内的产品个数作为候选N值的思想,有效地避免了推荐结果中被推荐产品间差异大,以及被推荐产品与不被推荐产品之间差异小的问题.论文构建了推荐系统中一般产品集团序模型,并针对N值大小进行了产品集团序质量评估,进而得到了可靠的N值.这一研究结果不仅丰富了推荐系统的理论成果,也为推荐输出的个性化研究探索了新的道路.
From the output functional of recommender systems, the issue of the top-N was researchedin this paper. The value of N affects the recommended quality and personalization. The teasibility and general methods of personalization of the output were studied in this paper. A new method based on aggregative rank was proposed. In the method, the entire sub-group is used as output of recommendation and the number of products in the sub-group is used as candidate value of N, in order to avoid big differences between the recommended products in the recommendation results and small differences between recommended products and un-recommended products. The general aggregative rank model of product was built in this paper. Meanwhile, aggregative rank quality was assessment based on different N, only in order to get a reliable value of N. The research results not only enrich the recommended system theoretical results, but also get a new road for personalization study of recommender systems.