Community Detection : Unsupervised Learning

Advances in technology and computation have provided the possibility of collecting and mining a massive amount of real-world data. Mining such “big data” allows us to understand the structure and the function of real systems and to find unknown and interesting patterns. This section provides the brief overview of the community structure. Introduction of Community Detection In the actual interconnected world, and the rising of online social networks the graph mining and the community detection become completely up-to-date. Understanding the formation and evolution of communities is a long-standing research topic in sociology in part because of its fundamental connections with the studies of urban development, criminology, social marketing, and several other areas. With increasing popularity of online social network services like Facebook, the study of community structures assumes more significance. Identifying and detecting communities are not only of particular importance but have immediate applications. For instance, for effective online marketing, such as placing online ads or deploying viral marketing strategies [10], identifying communities in social network could often lead to more accurate targeting and better marketing results. Albeit online user profiles or other semantic information is helpful to discover user segments this kind of information is often at a coarse-grained level…

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