Extended core-based community detection for directed networks
| Autor: | Amiya Nayak, Mohammad Rehaan, Anubhuti Garg |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Theoretical computer science
Degree (graph theory) Computer science Node (networking) Community structure 02 engineering and technology Directed graph computer.software_genre 01 natural sciences Compact space Similarity (network science) 020204 information systems 0103 physical sciences Core (graph theory) 0202 electrical engineering electronic engineering information engineering Data mining 010306 general physics Cluster analysis computer |
| Zdroj: | CITS |
| DOI: | 10.1109/cits.2017.8035342 |
| Popis: | The focus of this paper is on detecting overlapping communities for the directed graphs by implementing a new algorithm and analyzing it with various performance metrics. The algorithm aims at finding core nodes for the directed graph which are subset of communities and have higher contact frequency. These are then extended to find communities using compactness measurement (CM). The compactness of a node to the community is defined as the ratio of the outward degree of the node to the community to that of the total out degree of that node. Another approach that will be used to extend communities around core nodes is based on similarity measurement (SM) - two nodes are said to be similar if they share more mutual neighbours. We are able to achieve a success rate of 70% when CM is used and about 10–15% with SM based expansion method. The proposed algorithm is also compared with the existing method for community detection. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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