Social Relation Extraction of Large-Scale Logistics Network Based on MapReduce

Social network is a social structure of nodes that are linked by various kinds of relationships, such as friends, web links, etc. To extract social relation based on logistics data will contribute significantly to detect some underlying crimes. One of the main difficulties in social relation extraction from massive data is the low time efficiency. Fortunately, large scale parallel computation has been proved that it has an excellent capacity to cope with big data. In this paper, a MapReduce-based method was applied for extraction of social relation from logistics network using Hadoop platform. Experimental results showed that the proposed method improves the time efficiency well, and has more excellent scalability than traditional methods executed by a single machine.