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An improved topology-potential-based community detection algorithm for complex network.

Wang Z, Zhao Y, Chen Z, Niu Q - ScientificWorldJournal (2014)

Bottom Line: This hypothesis leads to inaccuracy of topology potential calculation and then decreases the precision of community detection.The more important the node is, the bigger its mass is.Simulation experiment results showed that, after taking node mass into consideration, the topology potential of node is more accurate, the distribution of topology potential is more reasonable, and the results of community detection are more precise.

View Article: PubMed Central - PubMed

Affiliation: School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China.

ABSTRACT
Topology potential theory is a new community detection theory on complex network, which divides a network into communities by spreading outward from each local maximum potential node. At present, almost all topology-potential-based community detection methods ignore node difference and assume that all nodes have the same mass. This hypothesis leads to inaccuracy of topology potential calculation and then decreases the precision of community detection. Inspired by the idea of PageRank algorithm, this paper puts forward a novel mass calculation method for complex network nodes. A node's mass obtained by our method can effectively reflect its importance and influence in complex network. The more important the node is, the bigger its mass is. Simulation experiment results showed that, after taking node mass into consideration, the topology potential of node is more accurate, the distribution of topology potential is more reasonable, and the results of community detection are more precise.

Show MeSH
Artificial complex network.
© Copyright Policy - open-access
Related In: Results  -  Collection


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fig2: Artificial complex network.

Mentions: The artificial complex network is generated by the LFR-Benchmark generator. The node number is 100, the edge number is 230, the average degree is 4.6, and the implanted community number is 2. The structure of the artificial complex network is shown in Figure 2.


An improved topology-potential-based community detection algorithm for complex network.

Wang Z, Zhao Y, Chen Z, Niu Q - ScientificWorldJournal (2014)

Artificial complex network.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3926370&req=5

fig2: Artificial complex network.
Mentions: The artificial complex network is generated by the LFR-Benchmark generator. The node number is 100, the edge number is 230, the average degree is 4.6, and the implanted community number is 2. The structure of the artificial complex network is shown in Figure 2.

Bottom Line: This hypothesis leads to inaccuracy of topology potential calculation and then decreases the precision of community detection.The more important the node is, the bigger its mass is.Simulation experiment results showed that, after taking node mass into consideration, the topology potential of node is more accurate, the distribution of topology potential is more reasonable, and the results of community detection are more precise.

View Article: PubMed Central - PubMed

Affiliation: School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China.

ABSTRACT
Topology potential theory is a new community detection theory on complex network, which divides a network into communities by spreading outward from each local maximum potential node. At present, almost all topology-potential-based community detection methods ignore node difference and assume that all nodes have the same mass. This hypothesis leads to inaccuracy of topology potential calculation and then decreases the precision of community detection. Inspired by the idea of PageRank algorithm, this paper puts forward a novel mass calculation method for complex network nodes. A node's mass obtained by our method can effectively reflect its importance and influence in complex network. The more important the node is, the bigger its mass is. Simulation experiment results showed that, after taking node mass into consideration, the topology potential of node is more accurate, the distribution of topology potential is more reasonable, and the results of community detection are more precise.

Show MeSH