Article
Weight Assignment on Edges Towards Improved Community Detection
IDEAS 2019: 23rd International Database Engineering & Applications Symposium
(2019)
Abstract
During the last few decades the problem of community detection in social networks has become an important and challenging computational task. Consequently, a number of algorithms have been proposed in the relevant literature, some of which seem to solve the problem quite efficiently. The huge amount of data, however, forces for further improved techniques that can handle large and complicated networks. In this paper, we consider the effect of assigning weights on edges of unweighted network graphs and estimate their importance in community detection. In particular, we propose a new edge weight function and study its effect when used as a preprocessing step for community detection algorithms. Experimental results on a benchmark of random networks confirm our intuition that assigning weights on edges can play an important role in improving the performance of such algorithms.
Disciplines
Publication Date
June, 2019
DOI
10.1145/3331076.3331121
Publisher Statement
SJSU users: Use the following link to login and access this article via SJSU databases.
Citation Information
Dora Souliou, Petros Potikas, Katerina Potika and Aris Pagourtzis. "Weight Assignment on Edges Towards Improved Community Detection" IDEAS 2019: 23rd International Database Engineering & Applications Symposium (2019) p. 1 - 5 Available at: http://works.bepress.com/aikaterini-potika/34/