Gravity Effects on Information Filtering and Network Evolving
Physics and Society
2015-06-16 v2 Information Retrieval
Social and Information Networks
Abstract
In this paper, based on the gravity principle of classical physics, we propose a tunable gravity-based model, which considers tag usage pattern to weigh both the mass and distance of network nodes. We then apply this model in solving the problems of information filtering and network evolving. Experimental results on two real-world data sets, \emph{Del.icio.us} and \emph{MovieLens}, show that it can not only enhance the algorithmic performance, but can also better characterize the properties of real networks. This work may shed some light on the in-depth understanding of the effect of gravity model.
Keywords
Cite
@article{arxiv.1306.4193,
title = {Gravity Effects on Information Filtering and Network Evolving},
author = {Jin-Hu Liu and Zi-Ke Zhang and Chengcheng Yang and Lingjiao Chen and Chuang Liu and Xueqi Wang},
journal= {arXiv preprint arXiv:1306.4193},
year = {2015}
}