Big Data Research ›› 2016, Vol. 2 ›› Issue (5): 32-42.doi: 10.11959/j.issn.2096-0271.2016052

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Cross-OSN user modeling in big data

Liancheng XIANG1,2,Jitao SANG1,2,Changsheng XU1,2   

  1. 1 Institute of Automation,Chinese Academy of Sciences,Beijing 100190,China
    2 University of Chinese Academy of Sciences,Beijing 100049,China
  • Online:2016-09-20 Published:2018-02-08
  • Supported by:
    The National Natural Science Foundation of China;The National Natural Science Foundation of China;The National Natural Science Foundation of China

Abstract:

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.

Key words: cross-OSN, user modeling, demographic attribute, interest attribute

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