中国物理B ›› 2017, Vol. 26 ›› Issue (12): 128901-128901.doi: 10.1088/1674-1056/26/12/128901

• INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY • 上一篇    

A uniform framework of projection and community detection for one-mode network in bipartite networks

Guolin Wu(吴果林), Changgui Gu(顾长贵), Lu Qiu(邱路), Huijie Yang(杨会杰)   

  1. 1. Business School, University of Shanghai for Science and Technology, Shanghai 200093, China;
    2. Faculty of Science, Guilin University of Aerospace Technology, Guilin 541004, China;
    3. Guangxi Aviation Logistics Research Center, Guilin University of Aerospace Technology, Guilin 541004, China;
    4. School of Finance and Business, Shanghai Normal University, Shanghai 200234, China
  • 收稿日期:2017-04-09 修回日期:2017-08-26 出版日期:2017-12-05 发布日期:2017-12-05
  • 通讯作者: Changgui Gu E-mail:gu_changgui@163.com
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant Nos. 11505114 and 10975099), the Program for Professor of Special Appointment (Orientational Scholar) at Shanghai Institutions of Higher Learning (Grant Nos. QD02015016 and DUSST02), the Shanghai Project for Construction of Discipline Peaks, the Natural Science Foundation of Guangxi Zhuang Guangxi Zhuang Autonomous Region (Grant No. 2016GXNSFDA380031), and the Fundamental Ability Enhancement Project for Young and Middle-aged University Teachers in Guangxi Zhuang Autonomous Region (Grant No. 2017KY0859).

A uniform framework of projection and community detection for one-mode network in bipartite networks

Guolin Wu(吴果林)1,2,3, Changgui Gu(顾长贵)1, Lu Qiu(邱路)4, Huijie Yang(杨会杰)1   

  1. 1. Business School, University of Shanghai for Science and Technology, Shanghai 200093, China;
    2. Faculty of Science, Guilin University of Aerospace Technology, Guilin 541004, China;
    3. Guangxi Aviation Logistics Research Center, Guilin University of Aerospace Technology, Guilin 541004, China;
    4. School of Finance and Business, Shanghai Normal University, Shanghai 200234, China
  • Received:2017-04-09 Revised:2017-08-26 Online:2017-12-05 Published:2017-12-05
  • Contact: Changgui Gu E-mail:gu_changgui@163.com
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant Nos. 11505114 and 10975099), the Program for Professor of Special Appointment (Orientational Scholar) at Shanghai Institutions of Higher Learning (Grant Nos. QD02015016 and DUSST02), the Shanghai Project for Construction of Discipline Peaks, the Natural Science Foundation of Guangxi Zhuang Guangxi Zhuang Autonomous Region (Grant No. 2016GXNSFDA380031), and the Fundamental Ability Enhancement Project for Young and Middle-aged University Teachers in Guangxi Zhuang Autonomous Region (Grant No. 2017KY0859).

摘要: Projection is a widely used method in bipartite networks. However, each projection has a specific application scenario and differs in the forms of mapping for bipartite networks. In this paper, inspired by the network-based information exchange dynamics, we propose a uniform framework of projection. Subsequently, an information exchange rate projection based on the nature of community structures of a network (named IERCP) is designed to detect community structures of bipartite networks. Results from the synthetic and real-world networks show that the IERCP algorithm has higher performance compared with the other projection methods. It suggests that the IERCP may extract more information hidden in bipartite networks and minimize information loss.

关键词: bipartite networks, community, projection, information exchange

Abstract: Projection is a widely used method in bipartite networks. However, each projection has a specific application scenario and differs in the forms of mapping for bipartite networks. In this paper, inspired by the network-based information exchange dynamics, we propose a uniform framework of projection. Subsequently, an information exchange rate projection based on the nature of community structures of a network (named IERCP) is designed to detect community structures of bipartite networks. Results from the synthetic and real-world networks show that the IERCP algorithm has higher performance compared with the other projection methods. It suggests that the IERCP may extract more information hidden in bipartite networks and minimize information loss.

Key words: bipartite networks, community, projection, information exchange

中图分类号:  (Structures and organization in complex systems)

  • 89.75.Fb
89.75.Hc (Networks and genealogical trees)