文章基本信息

标题：Position Based On Refining Aggregate Recommendation Assortment
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作者：L. Pravin Kumar ; Ramesh Krishnan
期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2015
卷号：4
期号：11
页码：14938-14941
DOI：10.18535/Ijecs/V4i1.09
出版社：IJECS
摘要：Recommendation systems are becoming necessary for individual user and also for providing recommendations atindividual level in various types of businesses. Recommender system is a personalized information filtering technique used toidentify desired number of items based on interest of user. The system uses data on past user ratings by applying varioustechniques. This techniques concentrate to improve accuracy in recommendations, with recommendation accuracy it is alsonecessary improve aggregate diversity of recommendation. In this paper, we proposed number of item ranking techniques anddifferent ratings prediction algorithm to improve recommendation accuracy and aggregate diversity by using real-world ratingdataset.
关键词：Recommender system; Recommendation;diversity; collaborative filtering; Ranking function