An improved algorithm for generalized community structure inference in complex networks

Qu, Yingfei; Shi, Wei; Shi, Xin

doi:10.1016/j.physa.2017.02.039

Cited by 2 publications

(1 citation statement)

References 15 publications

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“…Different communities have diverse characteristics which can complement each other. Because of its significance in social network analysis, lots of scholars in a variety of fields have paid attention to the identification of community structure and numerous classic methods have been developed to obtain optimal solutions, such as Girvan-Newman algorithm [32], VOS Clustering [33], topic oriented community detection approach [34], information-theoretic approach for detecting communities [35], degree-corrected block model [36], integrating center locating and membership optimization algorithm [37], and improved algorithm based on the random graph models [38], et al…”

Section: Introductionmentioning

confidence: 99%

Exploratory Key Nodes in the Inventor-author Knowledge Diffusion Network

Zhang

Wei

Shao

2018

Proceedings of the 51st Hawaii International Conference on System Sciences

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This paper aims to mine the key nodes in the process of knowledge flow from literatures of science and technology journals to technology patents on the community level. Based on the citation of technological patents to literatures of scientific journals and the cooperation among the researchers, this paper builds the knowledge flow network from the angle of spatial dimension. Then employing the extensity centrality-Newman and the commonly used degree indexes, this paper excavates and analyses the nodes which occupy important positions among communities in the knowledge flow network. After that, this paper puts forward suggestions on how to make full use of the key nodes' role of bridge to promote knowledge flow from literatures of science and technology journals to technology patents.

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