期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2016
卷号：7
期号：3
页码：1410-1413
出版社：TechScience Publications
摘要：Collaborative filtering (CF) is a techniquecommonly used to build personalized recommendationson the Web. Some popular websites that make use of thecollaborative filtering technology include Amazon,Netflix, iTunes, IMDB. Data sparseness is the mostimportant issue in CF. Data sparseness causes thesystem difficulty in determining the nearest neighboursof the target user accurately. Clustering can solve theproblem of data sparseness. Grouping a set of physicalor abstract objects into classes of similar objects, thisprocess is called as clustering. This paper presents themethods to generate recommendations using clusteringbasedcollaborative filtering approach.
关键词：Clustering; Collaborative filtering; Nearest;Neighbours; Data sparseness; Personalised;recommendations.
