In the current era of big data, high volumes of a wide variety of valuable data can be easily collected and generated from a broad range of data sources of different veracities at a high velocity. Due to the well-known 5V's of these big data, many traditional data management approaches may not be suitable for handling the big data. Over the past few years, several applications and systems have developed to use cluster, cloud or grid computing to manage big data so as to support data science, big data analytics, as well as knowledge discovery and data mining. In this paper, we focus on distributed big data management. Specifically, we present our method for big data representation and management of distributed big data from social networks. We represent such big graph data in distributed settings so as to support big data mining of frequently occurring patterns from social networks.
['Carson Kai-Sang Leung', 'Hao Zhang']
Management of Distributed Big Data for Social Networks