A parallel self-organizing overlapping community detection algorithm based on swarm intelligence for large scale complex networks
- Submitting institution
-
The University of West London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11003
- Type
- D - Journal article
- DOI
-
10.1016/j.future.2018.05.071
- Title of journal
- Future Generation Computer Systems
- Article number
- -
- First page
- 265
- Volume
- 89
- Issue
- -
- ISSN
- 0167-739X
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
7
- Research group(s)
-
-
- Citation count
- 4
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work is funded by Amazon Web Services Research Grant (US$10K) and four China national funding bodies. Community structure analysis is a critical task for complex network analysis. This paper is significant because the proposed new algorithm is the first effort on introducing swarm intelligence into complex community structure detection and analysis. The algorithm has been implemented on Amazon Clouds, and experimented for large-scale social network analysis for both synthesized and real-world networks (e.g. Amazon networks). The results show that the performance of proposed algorithm is superior to classic algorithms, and it can effectively discover network community structure.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -