Bi-Objective Community Detection (BOCD) in Networks using Genetic Algorithm

Computer Science – Social and Information Networks

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

11 pages, 3 Figures, 3 Tables. arXiv admin note: substantial text overlap with arXiv:0906.0612

Scientific paper

10.1007/978-3-642-22606-9_5

A lot of research effort has been put into community detection from all corners of academic interest such as physics, mathematics and computer science. In this paper I have proposed a Bi-Objective Genetic Algorithm for community detection which maximizes modularity and community score. Then the results obtained for both benchmark and real life data sets are compared with other algorithms using the modularity and MNI performance metrics. The results show that the BOCD algorithm is capable of successfully detecting community structure in both real life and synthetic datasets, as well as improving upon the performance of previous techniques.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Bi-Objective Community Detection (BOCD) in Networks using Genetic Algorithm does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Bi-Objective Community Detection (BOCD) in Networks using Genetic Algorithm, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Bi-Objective Community Detection (BOCD) in Networks using Genetic Algorithm will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-535253

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.