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Dividing a dataset into disjoint groups of homogeneous structure, known as data clustering, constitutes an important problem of data analysis. It can be solved with broad range of methods employing statistical approaches or heuristic procedures. The latter often include mechanisms known from nature as they are known to serve as useful components of effective optimizers. The paper investigates the...
The conventional algorithm (COPRA -- Community Overlap PRopagation Algorithm) proposed by Steve Gregory is efficient and useful in Complex Networks, but it is a challenge to select a suitable parameter "thr" as the input of the algorithm. In this paper, we put forward a threshold based label propagation algorithm, in which each vertex in the network is identified with a threshold respectively,...
Flower Pollination algorithm (FPA) is a new nature-inspired algorithm, based on the characteristics of flowering plants. In this paper, a new hybrid optimization method called quantum-behaved flower pollination algorithm (QFPA) is proposed. The method combines the standard Flower Pollination algorithm (FPA) with the quantum-behaved search mechanism to improve the global searching ability and accuracy...
How to identify community structure is a fundamental problem for analysis of complex network. In this paper we propose a novel similarity matrix of the nodes for this purpose, which combines the information of adjacency matrix and common-neighbors matrix. We compare it with diffusion kernel similarity and adjacency matrix using several algorithms which are widely used in detecting community structure,...
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