An Ensemble Approach to Discovering Evolving Communities in the Multidimensional Social Network
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 12
Abstract
Online Social network is growing to large extent to share information between the different diversity people around the world. The main objective of the proposed system to identify the community in the multidimensional data such as users , Tags , stories , locations ,employment details ,photos and comments . We propose a data mining technique to detect the frequently interacting users based on the common subjects and grouping them in single community. Unfortunately, the existing Community discover process-mining approaches do not take into account the hidden aspect of the intentions behind the data sharing in user activities, recognizing and detecting the hot topics in the network about public opinion on the focus of the community discovery. We assume that the intentional process models underlying user activities by using Intention mining techniques can discover the important information and entities as a community to gather the large members and exploit information’s. The aim of this paper is to propose the use of probabilistic models to evaluate the most likely intentions behind traces of unobserved activities and mixture information’s in the complex data structures between the multidimensional data, namely Discrete Hidden Markov Models (HMMs). Experiments based on synthetic and real-world data sets suggest that the proposed framework is able to find a community effectively. Experimental results have also shown that the performance of the proposed algorithm is better in accuracy than the other testing algorithms in finding communities in multi-dimensional networks.
Authors and Affiliations
Ms. I. Ajitha, Mrs. M. Vasanthi
Keywords
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