A Novel, Interdisciplinary, Approach for Community Detection Based on Remote File Requests
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. Therefor...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2018-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8528446/ |
| _version_ | 1818558472950644736 |
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| author | Stavros Souravlas Angelo Sifaleras Stefanos Katsavounis |
| author_facet | Stavros Souravlas Angelo Sifaleras Stefanos Katsavounis |
| author_sort | Stavros Souravlas |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-14T00:12:56Z |
| format | Article |
| id | doaj.art-d609e38186f94c2ba6b5449a5f8080cb |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T00:12:56Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-d609e38186f94c2ba6b5449a5f8080cb2022-12-21T23:25:41ZengIEEEIEEE Access2169-35362018-01-016684156842810.1109/ACCESS.2018.28801578528446A Novel, Interdisciplinary, Approach for Community Detection Based on Remote File RequestsStavros Souravlas0https://orcid.org/0000-0002-9602-2663Angelo Sifaleras1https://orcid.org/0000-0002-5696-7021Stefanos Katsavounis2Department of Applied Informatics, University of Macedonia, Thessaloniki, GreeceDepartment of Applied Informatics, University of Macedonia, Thessaloniki, GreeceDepartment of Production and Management Engineering, Democritus University of Thrace, Xanthi, GreeceCommunity 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.https://ieeexplore.ieee.org/document/8528446/Social networkscommunity detectiondistributed systemsdata replication |
| spellingShingle | Stavros Souravlas Angelo Sifaleras Stefanos Katsavounis A Novel, Interdisciplinary, Approach for Community Detection Based on Remote File Requests IEEE Access Social networks community detection distributed systems data replication |
| title | A Novel, Interdisciplinary, Approach for Community Detection Based on Remote File Requests |
| title_full | A Novel, Interdisciplinary, Approach for Community Detection Based on Remote File Requests |
| title_fullStr | A Novel, Interdisciplinary, Approach for Community Detection Based on Remote File Requests |
| title_full_unstemmed | A Novel, Interdisciplinary, Approach for Community Detection Based on Remote File Requests |
| title_short | A Novel, Interdisciplinary, Approach for Community Detection Based on Remote File Requests |
| title_sort | novel interdisciplinary approach for community detection based on remote file requests |
| topic | Social networks community detection distributed systems data replication |
| url | https://ieeexplore.ieee.org/document/8528446/ |
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