Journal of Computer Applications ›› 2019, Vol. 39 ›› Issue (3): 899-906.DOI: 10.11772/j.issn.1001-9081.2018071628

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Discovery algorithm for overlapping enterprise community with kernel based on node mapping

LU Zhigang, HU Xinchen   

  1. College of Economics and Management, Shanghai Maritime University, Shanghai 201306, China
  • Received:2018-08-06 Revised:2018-09-02 Online:2019-03-10 Published:2019-03-11
  • Supported by:

    This work is partially supported by the Natural Science Foundation of Shanghai (18ZR1416900).


卢志刚, 胡昕晨   

  1. 上海海事大学 经济管理学院, 上海 201306
  • 通讯作者: 胡昕晨
  • 作者简介:卢志刚(1973-),男,湖北荆门人,教授,博士,主要研究方向:大数据分析、商务智能、供应链管理;胡昕晨(1994-),女,山东滕州人,硕士研究生,主要研究方向:大数据分析、商务智能。
  • 基金资助:



As most existing enterprise community discovery algorithms focus on homogenous market environment, without reflecting the participation of some enterprises in multiple supply chain operations, a core community representation model based on node mapping relationship, Map-Community, was proposed. By constructing two different role nodes and their different mapping relationships, the ownership community of a enterprise was determined. Based on this representation model, Node Mapping Algorithm (NMA) with approximately-linear time-space complexity was proposed. Firstly, filtering operation was used to obtain the biconnected core graph in the topology diagram of the supply chain network. Secondly, mapping degree was introduced to select the core enterprise nodes. Thirdly, local expansion was performed according to the mapping judgment rules. Finally, the local community structure was extended to the global network by backtracking and overlapping areas were discovered. In the LFR (Lancichinetti-Fortunato-Radicchi) network application experiment, NMA shows low sensitivity to threshold change and is superior to LFM (Local Fitness Maximization), COPRA (Community Overlap PRopagation Algorithm) and GCE (Greedy Clique Expansion) in terms of practicality. Simulation was carried out in the enterprise social network, and the meaning of distribution effect was summarized by the community division. The experimental results verify the feasibility of this algorithm for overlapping enterprise community discovery and its performance advantages in discovery quality.

Key words: node mapping, biconnected core graph, core enterprise, local expansion, overlapping enterprise community discovery



关键词: 节点映射, 双连通核心图, 核心企业, 局部扩展, 企业重叠社群发现

CLC Number: