跨社交媒体网络大数据下的用户建模  

Cross-OSN user modeling in big data

作　　者：项连城 桑基韬[1,2] 徐常胜[1,2] 

机构地区：[1]中国科学院自动化研究所,北京100190 [2]中国科学院大学,北京100049

出　　处：《大数据》2016年第5期32-42,共11页Big Data Research

基　　金：国家自然科学基金资助项目(No.61432019;No.61225009;No.61303176)~~

摘　　要：社交媒体大数据中的多源性体现在不同社交媒体网络产生的内容上,从多源的角度分析跨社交媒体网络可以将独立数据的价值通过整合其他来源和模态的数据充分挖掘和释放出来,提高大数据的利用效率。跨社交媒体网络的用户建模是分析和应用多源社交媒体大数据的重要体现。跨社交媒体网络中的多源数据共享独立用户空间,提出以用户为桥梁对多源数据进行关联挖掘,将挖掘得到的关联模式分别应用于跨社交媒体网络的用户人口属性建模和兴趣建模中,并应用到社交媒体应用的个性化服务中。Social media variety mainly concerns with the contents created and consumed in different online social network（OSN）. Analyzing cross-OSN from the perspective of ＂variety＂ is beneficial to exerting the potential of big data, by integrally analyzing and exploiting the multi-sourced and multi-modal data. The problem of exploiting the cross-OSN data for comprehensive user modeling, which is fundamental in the context of multi-sourced social media big data was addressed. Inspired by the fact that the cross-OSN data shares unique user space, take the users as a bridge for associations mining between OSN was proposed. The discovered association patterns were then utilized in cross-OSN user demographic attribute inference and interest modeling in cross-OSN respectively, which can be further applied to personalized social media services.

关 键 词：跨社交媒体网络 用户建模 人口属性 兴趣属性 

分 类 号：TP37[自动化与计算机技术—计算机系统结构]