期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2013
卷号：4
期号：3
页码：549-552
语种：English
出版社：Ayushmaan Technologies
摘要：Extensive contents generation in web becoming a challenging task to the recent researchers. This explosive content increased the demand of recommendation technique usage to reach the users service. We use different kind of recommendation in web every day including music, movies, images, books, tag recommendation etc. irrespective of data model used in recommendation it can be modeled in the form of various types of graph. In this paper, we first propose a diffusion method which propagates similarities between different nodes and generates recommendations; and then we illustrate how to generalize different recommendation problems into our graph diffusion. This proposed framework can be utilized in any recommendation tasks on the Web.
