Date of Award
2017
Publication Type
Master Thesis
Degree Name
M.Sc.
Department
Computer Science
Keywords
Community Detection, Dynamic Social Networks, Knowledge Sharing, Multi-Population Cultural Algorithm, Prior Knowledge
Supervisor
Kobti, Ziad
Rights
info:eu-repo/semantics/openAccess
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Abstract
The relationship between a community and the knowledge that it encompasses is a fundamentally important aspect of any social network. Communities, with some level of similarity, implicitly tend to have some level of similarity in their knowledge as well. This work does the analysis on the role of prior knowledge in Multi-Population Cultural Algorithm (MPCA) for community detection in dynamic social networks. MPCA can be used to find the communities in a social network. The knowledge gained in this process is useful to analyze the communities in other social networks having some level of similarity. Our work assumes that knowledge is an integral part of any community of a social network and plays a very important role in its evolution. Different types of networks with levels of non-similarity are analyzed to see the role of prior knowledge while finding communities in them.
Recommended Citation
Pandey, Mukund, "The Role of Prior Knowledge in Multi-Population Cultural Algorithms for Community Detection in Dynamic Social Networks" (2017). Electronic Theses and Dissertations. 6007.
https://scholar.uwindsor.ca/etd/6007