一种基于用户信任网络的物质扩散推荐算法

doi:10.3969/j.issn.1006-2475.2018.02.003

计算机与现代化

一种基于用户信任网络的物质扩散推荐算法

（河海大学计算机与信息学院,江苏南京211100）

收稿日期:2017-06-07 出版日期:2018-03-08 发布日期:2018-03-09
作者简介:梁艺(1994-),男,河北平乡人,河海大学计算机与信息学院硕士研究生,研究方向:推荐系统,数据挖掘；韩立新(1967-),男,江苏南京人,博士生导师,博士,研究方向:信息检索,模式识别,数据挖掘。

A Mass Diffusion Recommender Algorithm with User Trust Network

(College of Computer and Information, Hohai University, Nanjing 211100, China)

Received:2017-06-07 Online:2018-03-08 Published:2018-03-09

摘要/Abstract

摘要： 在推荐系统中，构建资源模型是一个关键问题。通过对以往传统基于用户的资源模型研究，发现其往往假定用户独立存在，未能充分利用用户之间的信任关系，这带来马太效应过强，冷启动难等问题。基于此，本文设计一种基于标签共现的用户信任网络，通过在其上执行PageRank算法对基于用户的资源模型进行更新优化，进而结合经过改进的物质扩散算法得出推荐结果。实验表明，相较于以往算法，本文提出的算法较为显著地提高了推荐效果。

关键词: 资源模型, 信任网络, 标签, 物质扩散, 推荐系统

Abstract: In the recommend systems, modeling resource is a vital issue. Based on the study of the traditional user-based resource models, we find that it is always assumed that users are independent of each other, trust relations among the users are not fully used, leading to strong Matthew effect, cold start problem and so on. This paper designs a common user trust network based on the tag co-occurrence, upon which the PageRank algorithm is used to refine the resource model. Further, an improved diffusion process is performed to get the recommend results. Compared with the previous algorithms, experimental results show that our algorithm significantly improves accuracy， recall and F1-measure of recommendations.

Key words: resource model, trust network, tag, mass diffusion, recommender system

中图分类号:

TP391

梁艺，韩立新. 一种基于用户信任网络的物质扩散推荐算法[J]. 计算机与现代化, doi: 10.3969/j.issn.1006-2475.2018.02.003.

LIANG Yi, HAN Li-xin. A Mass Diffusion Recommender Algorithm with User Trust Network[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2018.02.003.

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一种基于用户信任网络的物质扩散推荐算法

A Mass Diffusion Recommender Algorithm with User Trust Network

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