کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
978464 | 933281 | 2009 | 5 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Collaborative filtering based on multi-channel diffusion Collaborative filtering based on multi-channel diffusion](/preview/png/978464.png)
In this paper, by applying a diffusion process, we propose a new index to quantify the similarity between two users in a user–object bipartite graph. To deal with the discrete ratings on objects, we use a multi-channel representation where each object is mapped to several channels with the number of channels being equal to the number of different ratings. Each channel represents a certain rating and a user having voted an object will be connected to the channel corresponding to the rating. Diffusion process taking place on such a user–channel bipartite graph gives a new similarity measure of user pairs, which is further demonstrated to be more accurate than the classical Pearson correlation coefficient under the standard collaborative filtering framework.
Journal: Physica A: Statistical Mechanics and its Applications - Volume 388, Issue 23, 1 December 2009, Pages 4867–4871