网络媒体大数据中的异构网络对齐关键技术和应用研究

A Survey of Key Technologies and Applications on Heterogeneous Network Alignment in Social Network Big Data

大量社会媒体网络平台的广泛使用带来网络媒体大数据。单网络上的用户数据往往具有分布不均衡、噪音大、动态变化强、质量良莠不齐等特点,异构网络对齐成为多源数据融合、挖掘网络媒体大数据价值的首要前提。通过对异构网络对齐的国内外研究现状进行综述,从计算因素的角度阐述了异构网络主要技术路线,并对其应用研究现状进行分析。最后,指出面临的挑战问题,为网络媒体大数据研究者们提供参考。

More online social network platforms offer more services for users, which brings so- cial network big data. The data set about users is always full of noise, unbalance and dynamic. Heterogeneous network alignment becomes a key work for fusing multi-resource data. This arti- cle gives a survey on the key technologies and applications of heterogeneous networks alignment. Some challenges are pointed out at the end. All of this will provide useful reference for research- ers on social network big data.