综述述评

个性化推荐系统的多样性研究进展

  • 安维 ,
  • 刘启华 ,
  • 张李义
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  • 1. 武汉大学信息管理学院;
    2. 江西财经大学信息管理学院
安维,武汉大学信息管理学院博士研究生;张李义,武汉大学信息管理学院教授,博士生导师.

收稿日期: 2013-09-02

  修回日期: 2013-10-02

  网络出版日期: 2013-10-20

基金资助

本文系国家自然科学基金项目"泛在环境下基于情境历史和兴趣社区的个性化信息推荐模型与实现"(项目编号:71363022)和国家自然科学基金项目"融合情境的移动阅读推荐系统研究"(项目编号:71373192)研究成果之一。

Review on Diversity in Personalized Recommender Systems

  • An Wei ,
  • Liu Qihua ,
  • Zhang Liyi
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  • 1. School of Information Management, Wuhan University, Wuhan 430072;
    2. School of Information Technology, Jiangxi University of Finance and Economics, Nanchang 330013

Received date: 2013-09-02

  Revised date: 2013-10-02

  Online published: 2013-10-20

摘要

在分析多样性类型的基础上,重点对信息物理、二次优化、社会化网络和时间感知4种提高个性化推荐多样性的方法进行概括、比较和分析,接着总结推荐系统多样性的主要度量指标。最后,对未来有等深入研究的问题进行展望。研究指出:移动推荐系统的多样性和新颖性研究,信息物理方法应用于推荐系统领域的机理分析,推荐系统的时序多样性和计算量问题以及各种推荐算法的有效组合研究是未来需重点突破的方向。

本文引用格式

安维 , 刘启华 , 张李义 . 个性化推荐系统的多样性研究进展[J]. 图书情报工作, 2013 , 57(20) : 127 -135 . DOI: 10.7536/j.issn.0252-3116.2013.20.022

Abstract

This paper presents an overview of diversity in personalized recommender technology from three dimensions including the types of diversity, four methods to improve the recommendation diversification which contain information-physics, quadratic optimization, social networking, time-aware recommendation, and evaluated metrics of diversity. The prospects for future development and suggestions for possible extensions are as follows: novelty and diversity in mobile recommender systems, the mechanism analysis of internet-based information-physics in recommender systems, temporal diversity and the amount of computation in recommender systems and the effective combination of various recommendation algorithms.

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