Detecting Overlapping Nodes In MLM Network Chain to Cluster Serval Communities

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2016 by IJCTT Journal
Volume-42 Number-2
Year of Publication : 2016
Authors : Miss Sukhada B. Vader, Mrs. Mugdha Kirkire
  10.14445/22312803/IJCTT-V42P115

MLA

Miss Sukhada B. Vader, Mrs. Mugdha Kirkire  "Detecting Overlapping Nodes In MLM Network Chain to Cluster Serval Communities". International Journal of Computer Trends and Technology (IJCTT) V42(2):90-93, December 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
The Detecting Overlapping Node Structure a connection based algorithm proposed for discovering high quality overlapping structures in MLM Chain networks. Proposed method is fast, very limited parameter dependent and only requires local knowledge about the network chain. Furthermore, the community structures discovered is deterministic, i.e., no fuzzy community assignments are produced. The demonstrative benchmark with other detection methods highlights the efficiency of algorithm when discovering community structures of large-scale networks. By using DONS to analyze the community structures of real datasets, we find that overlapping communities occur naturally and quite frequently, especially for top largest communities. In addition, overlapped nodes tend to be active users who participate in multiple networks at the same time. Discovery of natural groups of similarly functioning individuals is a key task in analysis of real world networks. Here we introduce an approach to identify overlapping structure based on an efficient algorithm. In our method, communities are formed by adding peripheral nodes to cores. Therefore, communities are allowed to overlap. We show experimental studies on synthetic networks to demonstrate that our method has excellent performances in community detection.

References
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Keywords
Chain networks,Community,Overlapping,Aggregation, Information Extraction.