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HOCTracker: Tracking the Evolution of Hierarchical and Overlapping Communities in Dynamic Social Networks
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HOCTracker: Tracking the Evolution of Hierarchical and Overlapping Communities in Dynamic Social Networks

Category : Data Mining


Sub Category : DOTNET


Project Code : ITDDM04


Project Abstract

HOCTRACKER: TRACKING THE EVOLUTION

OF HIERARCHICAL AND OVERLAPPING

COMMUNITIES IN DYNAMIC SOCIAL NETWORKS

ABSTRACT

In this paper, we propose a unified framework, HOC Tracker, for tracking the evolution of hierarchical and overlapping communities in online social networks. Unlike most of the dynamic community detection methods, HOC Tracker adapts preliminary community structure towards dynamic changes in social networks using a novel density-based approach for detecting overlapping community structures, and automatically tracks evolutionary events like birth, growth, contraction, merge, split, and death of communities. It uses a novel and efficient log-based approach to map evolutionary relations between communities identified at two consecutive time-steps of a dynamic network, which considerably reduces the number of community comparisons. Moreover, it does not require an ageing function to remove old interactions for identifying community evolutionary events. HOC Tracker inapplicable to undirected and weighted networks. Experimental results have shown that community structures identified by HOC Tracker on some well-known benchmark networks are significant and in general better that the community structures identified by the state-of-the-art methods.

 

 

 

 

 

 

 

 

 

EXISTING SYSTEM

PROPOSED SYSTEM

 EXISTING CONCEPT:-

In this case, a previous noncore node (including an outlier or a newly added node) in the network becomes a core node. Such anew core node p may either join the MCMS of an existing community causing its expansion, form atonally new community (birth), or may cause two communities to merge by joining their respective MCMSs through its Np. These situations are generalized.

Existing core node loses its core node property due to some change(s) in its neighborhood. Such a situation could either split a community due to a cut in its MCMS resulting from a lost core node, or shrinkage of a community. These situations are generalized.

 PROPOSED CONCEPT:-

In this paper, we have proposed a novel density-based framework, HOC Tracker, to track community evolution in dynamic social networks.

The problem of community detection in social networks depends on various factors, including whether the definition of community relies on global or local network properties, whether communities overlap, whether communities possess a hierarchical structure, whether link weights are utilized, whether outliers are considered, and whether dynamic nature of networks/communities is considered.

EXISTING TECHNIQUE:-

Birth_Expand_Merge,Death_Shrink_Split, Crawl

PROPOSED TECHNIQUE:-

HOC Tracker

 

TECHNIQUE DEFNITION:-

Existing core node loses its core node property due to some change(s) in its neighborhood. Such a situation could either split a community due to a cut in its MCMS resulting from a lost core node, or shrinkage of a community. These situations are generalized.

TECHNIQUE DEFNITION:-

Real-world social networks often contain noise or outliers and hubs. Therefore, after finding all possible communities from an underlying network, HOC Tracker labels an un-clustered/un-labeled node as a hub if it has out-going edges to the primary core nodes of more than one community, and the remaining nodes are marked as outliers.

DRAWBACKS:-

Here existing community can access new  community

existing community content will be change

ADVANTAGES:-

Here easily find out the overlapping

Content doesn’t change

 
 
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