节点文献
面向大社交数据的深度分析与挖掘
Deep analytics and mining for big social data
【摘要】 社交网络在线化是大数据时代的典型特点,也是大数据产生的重要原因之一.本文从大数据的特点着手,结合互联网络尤其是在线社交网络的发展趋势,介绍大数据在提升国家信息产业科学化水平、引领新型互联网经济发展、推动社会学与信息科学交叉发展等方面带来的重大机遇;分析在线社会网络中存在的关键问题,阐述网络大数据研究在语义理解与分析、多模态关联与融合、群体行为分析与挖掘、多维分析与可视化、系统的研发与集成等方面面临的巨大技术挑战,以及当前国内外在大数据分析和在线社交网络领域的主要研究工作;总结和展望网络大数据研究的未来方向和前景.
【Abstract】 Online social networking is one of the most prominent features and main reasons of the big data era. In this paper, we first present the immense opportunities brought by big data in: advancing the technical level of the Chinese IT industry, leading development of the new Internet economy, and accelerating interdisciplinary research between sociology and information science. Next we analyze key issues in online social networks and point out new challenges of big social data research on semantic understanding and analysis, multi-modal association and fusion, group behavior analysis and mining, multidimensional analysis and visualization, and system development and integration. We then focus on introducing key international and domestic achievements in big data and online social networks. We conclude with a look at future trends in big social data analytics and mining.
【Key words】 social network; social influence; community discovery; social behavior prediction;
- 【文献出处】 科学通报 ,Chinese Science Bulletin , 编辑部邮箱 ,2015年Z1期
- 【分类号】TP393.09
- 【被引频次】38
- 【下载频次】1863