[1]王大玲,冯时,张一飞,等.社会媒体多模态、多层次资源推荐技术研究[J].智能系统学报,2014,9(3):265-275.[doi:10.3969/j.issn.1673-4785.201403068]
　WANG Daling,FENG Shi,ZHANG Yifei,et al.Study on the recommendations of multi-modal and multi-level resources in social media[J].CAAI Transactions on Intelligent Systems,2014,9(3):265-275.[doi:10.3969/j.issn.1673-4785.201403068]
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社会媒体多模态、多层次资源推荐技术研究

《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷: 9 期数: 2014年第3期 页码: 265-275 栏目: 学术论文—智能系统 出版日期: 2014-06-25
Title:
Study on the recommendations of multi-modal and multi-level resources in social media
作者:
王大玲1,2, 冯时1,2, 张一飞1,2, 于戈1,2
1. 辽宁石油化工大学 信息与控制工程学院, 辽宁 抚顺 113001;
2. 东北大学 医学影像计算教育部重点实验室, 辽宁 沈阳 110819
Author(s):
WANG Daling1,2, FENG Shi1,2, ZHANG Yifei1,2, YU Ge1,2
1. School of Information Science and Engineering, Northeastern University, Shenyang 110819, China;
2. Key Laboratory of Medical Image Computing (Northeastern University), Ministry of Education, Shenyang 110819, China
关键词:
社会媒体; 推荐; 多模态信息; 多层次资源; 用户社群
Keywords:
social media; recommendation; multi-modal information; multi-level resource; user community
分类号:
TP301
DOI:
10.3969/j.issn.1673-4785.201403068
摘要:
社会媒体中多模态和多层次的信息资源和基于各种关系构建的用户社群为推荐系统提供了更广阔的分析和选择空间, 同时也带来了更多的问题与挑战。分析了当前社会媒体中用户与资源的关系以及社会媒体资源推荐的特点, 分别从社会媒体资源推荐策略和相关支撑技术两方面综述了相关工作, 将其概括为"社会媒体中用户角色的变化构成了更加复杂的用户关系"、"社会媒体资源表示形式呈现多模态特点"以及"社会媒体资源推荐应该满足多层次的用户需求", 并从多模态、多层次资源推荐方面提出进一步的研究方向。
Abstract:
The multi-modal and multi-level information resources and user communities based on various relationships in social media provide a broader space for recommenders to analyze and select the resources, but at the same time more problems and challenges develop. In this paper, the relationships between users and resources, and the characteristics of resource recommendations in current social media are analyzed. Related work is surveyed from social media resource recommendations as well as its corresponding support techniques, which can be summarized as follows: more complex relationships among users formed by changes of user roles, multi-modal social media resource expressions, and social media resource recommendations that satisfy the requirements of multi-level users. Finally, further research directions in multi-modal and multi-level resource recommendations are proposed.
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备注/Memo

收稿日期:2014-03-25。
基金项目:国家自然科学基金资助项目(61370074, 61100026)
作者简介:冯时,男,1981年生,讲师,主要研究方向情感挖掘、网络舆情分析;张一飞,女,1977年生,讲师,主要研究方向为图像处理、多媒体数据挖掘。
通讯作者:王大玲,女,1962年生,教授,中国计算机学会高级会员,中国计算机学会中文信息技术专业委员会委员,主要研究方向为数据挖掘、信息检索、Web推荐等,主持国家自然科学基金项目3项,参与国家自然科学基金项目2项,E-mail:wangdaling@ise.neu.edu.cn。

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