Analyzing community structure based on topology potential over complex network system

Kanokwan Malang*, Shuliang Wang, Tianru Dai

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Community structure is one of complex network properties which reveals the main organizing proposition in most real-world complex networks. The special interests are groups of vertices within the intense edges or connections that are not only overlapping, but also change over-time. In this paper, we present the overview of structured complex network properties that affect the process of discovering community structure. Topology potential of nodes in complex network is also described. Topology potential is a measurement method to investigate the interaction among community members. From the recent literatures, the community structure discovered by topology potential needs to be improved in term of performance and accuracy in order to obtain more meaningful results.

Original languageEnglish
Title of host publicationGeo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers
EditorsHanning Yuan, Jing Geng, Chuanlu Liu, Tisinee Surapunt, Fuling Bian
PublisherSpringer Verlag
Pages56-68
Number of pages13
ISBN (Print)9789811308956
DOIs
Publication statusPublished - 2018
Event5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017 - Chiang Mai, Thailand
Duration: 8 Dec 201710 Dec 2017

Publication series

NameCommunications in Computer and Information Science
Volume849
ISSN (Print)1865-0929

Conference

Conference5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017
Country/TerritoryThailand
CityChiang Mai
Period8/12/1710/12/17

Keywords

  • Community structure
  • Complex network
  • Topology potential

Fingerprint

Dive into the research topics of 'Analyzing community structure based on topology potential over complex network system'. Together they form a unique fingerprint.

Cite this