Document Type
Contribution to a Book
Publication Date
4-28-2019
Publication Title
Algorithmic Aspects of Cloud Computing. ALGOCLOUD 2018
Editor
Yann Disser, Vassilios S. Verykios
First Page
13
Last Page
24
ISBN
978-3-030-19759-9
Abstract
Most social networks of today are populated with several millions of active users, while the most popular of them accommodate way more than one billion. Analyzing such huge complex networks has become particularly demanding in computational terms. A task of paramount importance for understanding the structure of social networks as well as of many other real-world systems is to identify communities, that is, sets of nodes that are more densely connected to each other than to other nodes of the network. In this paper we propose two algorithms for community detection in networks, by employing the neighborhood overlap metric and appropriate spanning tree computations.
Recommended Citation
Ketki Kulkarni, Aris Pagourtzis, Katerina Potika, Petros Potikas, and Dora Souliou. "Community Detection via Neighborhood Overlap and Spanning Tree Computations" Algorithmic Aspects of Cloud Computing. ALGOCLOUD 2018 (2019): 13-24. https://doi.org/10.1007/978-3-030-19759-9_2
Included in
Numerical Analysis and Scientific Computing Commons, OS and Networks Commons, Systems Architecture Commons
Comments
This is a post-peer-review, pre-copyedit version of an article published in Algorithmic Aspects of Cloud Computing. ALGOCLOUD 2018. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-19759-9_2
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