Computing the Minimalistic Graph of Interest in Social Media Mining using CHG Algorithm

Social network is a dedicated website or other application which enables users to communicate with each other by posting information, comments, messages, images, etc. By using a Social Network Analysis (SNA) approach, it helps to relate to the known members of the group, but the current approach leads to a much higher complexity and lacks the efficiency in producing the new Graph of interest (GOI). This paper presents a new approach in order to compute the minimalistic graph. We calculate the structural relationship between the members of the graph with the help of assigning weights to different relations and the region to reside, using a tight constraint calculation. By forming such relationships we can extract the GOI which allows us to find the most relevant nodes within the graph which are essential for a lot of practical approaches. These nodes are found with the help of the Controlled Heuristic Graph (CHG) function and using this, the efficiency of finding the relevant nodes in a given graph can be improved resulting in a better minimalistic graph. Keywords - Graph of interest (GOI), one billion graph, independent relative importance (iRI).