Social Network Analysis Using Novel Graph Mining Approach
Graph mining is a popular topic in research area. Social networks are often modeled as graphs in which a node denotes a person, and an edge indicates some relationship, e.g., in Facebook, Twitter and LinkedIn. In the actual interconnected world, and the rising of online social networks the graph mining and the community detection become completely up-to-date. Finding groups with high concentrations of relations within the group and low concentration between these groups, which is called community detection.There are three main parts in graph mining Mining frequent subgraph patterns, graph indexing and graph similarity search. And there are two main approaches for the subgraph pattern mining: Apriori-Based Approach and Pattern-Growth Approach .Graph pattern matching used for graph clustering, graph indexing.
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