Earticle

초록

영어

This paper introduces a new multi-view and controllable community-uncovering algorithm, an achievement of improving PageRank algorithm and Spin-glass model, which can avoid the overlapping community structure in the process of detecting communities by means of other algorithms and also helps to improve the usual community-expansion model.The process of uncovering communities by the introduced algorithms can be divided into three steps: first, identifying the nuclear one among nodes ranked by the advanced PageRank algorithms; Second, through using multi-view recognition modularity provided by Potts spin-glass model, optimizing the expansion model of local community that is found by applying the improved Iterative Greedy algorithm to eliminate the traditional modularity’s limits in the resolution limit and the following negative effects. Finally, grasping the overlapping structure and notes carefully. By analyzing and comparing the two results of respectively using PRSGMFCA and traditional technical schemes in both computer simulation network and the real network, it proves that the former enjoys stronger stability and higher accuracy than the latter, and its computation complexity is also acceptable.

목차

Abstract
 1. Introduction
 2. Algorithms
 3. Experiments and Performance Analysis
 4. Conclusion
 References

키워드

저자

• Zhang Xin [ Harbin Institute of Technology, school of Computer Science and Technology, Harbin, China ]
• Wang Xiaolong [ Harbin Institute of Technology, school of Computer Science and Technology, Harbin, China ]
• Liu Bingquan [ Harbin Institute of Technology, school of Computer Science and Technology, Harbin, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605