压缩和挖掘社交网络数据

Connor C. J. Hryhoruk, C. Leung
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引用次数: 5

摘要

如今,社交网络很受欢迎。因此,许多社交网站(如Facebook、YouTube、Instagram)正在迅速产生大量的社交数据。有价值的知识和信息被嵌入到这些大的社会数据中。由于社交网络可能非常稀疏,因此它需要(a)通过社交网络数据压缩进行压缩,(b)通过社交网络分析和挖掘进行分析和挖掘。本文提出了一种压缩和挖掘社交网络的解决方案。它给出了稀疏社会网络的可解释压缩表示,并从中发现有趣的模式。我们的评估结果表明我们的解决方案在解释稀疏社会网络数据的压缩和挖掘方面是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Compressing and mining social network data
Nowadays, social networking is popular. As such, numerous social networking sites (e.g., Facebook, YouTube, Instagram) are generating very large volumes of social data rapidly. Valuable knowledge and information is embedded into these big social data. As the social network can be very sparse, it is awaiting to be (a) compressed via social network data compression and (b) analyzed and mined via social network analysis and mining. We present in this paper a solution for compressing and mining social networks. It gives an interpretable compressed representation of sparse social network, and discovers interesting patterns from the social network. Results of our evaluation show the effectiveness of our solution in explaining the compression and mining of the sparse social network data.
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