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Title: A Novel, Interdisciplinary, Approach for Community Detection Based on Remote File Requests
Authors: Souravlas, Stavros
Sifaleras, Angelo
Katsavounis, Stefanos
Type: Article
Subjects: FRASCATI::Natural sciences::Computer and information sciences
FRASCATI::Engineering and technology::Electrical engineering, Electronic engineering, Information engineering
Keywords: Social networks
Community detection
Distributed systems
Data replication
Issue Date: 2018
Publisher: IEEE
Source: IEEE Access
Volume: 6
First Page: 68415
Last Page: 68428
Abstract: Community structures are formed in many real-world networks, e.g., biological or medical groups, student groups, and so on. Communities are perhaps the most important feature of today's networks, since the majority of people who join a network also tend to join one or more communities. Therefore, several researchers find that the detection of hidden communities is a very interesting and challenging research field. Communities are represented as the groups of nodes on a graph, corresponding to users with similar interests. This paper introduces a novel, interdisciplinary, approach for community detection, combining social networks and distributed systems, where remote access to shared files is offered in a networked environment. A new metric, based on data requests, is introduced and used as a measure of the belonging degree of a node in a certain formed community. Two sets of simulations are used to verify our scheme: simulation results on synthetic networks and results derived from real data.
ISSN: 2169-3536
Other Identifiers: 10.1109/ACCESS.2018.2880157
Appears in Collections:Department of Applied Informatics

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