Asogwa, Jonas (2022) Detecting Overlapping Communities in ISEBEL. Universität Rostock, Institut für Informatik.
|
Text
MA-Asogwa-final-20220517.pdf Download (1MB) | Preview |
Abstract
Real-world complex networks are evident in the social networks, the internet, and biological networks. The complexities of most real-world networks make them have community structures that can be divided into subgroups based on some statistical features or how strongly the vertices are closely connected. A vertex may be a member of more than one community, resulting in overlapping communities in such a real-world network. The ISEBEL story network is yet another complex network with varieties of folklore of werewolves, witches, and legends which form communities with overlapping vertices. Many algorithms for detecting overlapping communities in real-world networks exist. In this work, we propose a framework built on Apache spark using the BigClam algorithm that is able to detect overlapping communities in ISEBEL dataset.
| Item Type: | Other |
|---|---|
| Subjects: | Projekte > ISEBEL Autorenart > Studentische Arbeiten > Masterarbeit Autorenart > Studentische Arbeiten |
| Depositing User: | Dbis Admin |
| Date Deposited: | 13 Jun 2022 06:49 |
| Last Modified: | 13 Jun 2022 06:49 |
| URI: | https://eprints.dbis.informatik.uni-rostock.de/id/eprint/1075 |
Actions (login required)
 |
View Item |
