Creating a Maximal Clique Graph to Improve Community Detection in SCoDA and OSLOM Algorithms
Community detection is one of the important topics regarding complex network study. There are many community detection algorithms such as Streaming Community Detection Algorithm (SCoDA) and Order Statistics Local Optimization Method (OSLOM). However, the performance of these algorithms, in overlap c...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Iran Telecom Research Center
2019-12-01
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| Series: | International Journal of Information and Communication Technology Research |
| Subjects: | |
| Online Access: | http://ijict.itrc.ac.ir/article-1-447-en.html |
| _version_ | 1811169264946642944 |
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| author | Sasan Sabour Ali Moeini |
| author_facet | Sasan Sabour Ali Moeini |
| author_sort | Sasan Sabour |
| collection | DOAJ |
| description | Community detection is one of the important topics regarding complex network study. There are many community detection algorithms such as Streaming Community Detection Algorithm (SCoDA) and Order Statistics Local Optimization Method (OSLOM). However, the performance of these algorithms, in overlap communities and communities with ambiguous structure, is problematic. In community detection algorithms achieving accurate results is a challenge. In this paper, we’ve proposed a method based on finding maximal cliques and generating the corresponding graph in order to use as an input to SCoDA and OSLOM algorithms. Synthetic non-overlap and overlap graphs and real graphs data are used in our experiments. F1score and NM1 score functions are utilized as our evaluation criteria. We have shown that the improved version of SCoDA demonstrated better results in comparison to the original SCoDA algorithm, and the improved version of OSLOM was also superior in performance when compared with the original OSLOM algorithm. |
| first_indexed | 2024-04-10T16:40:33Z |
| format | Article |
| id | doaj.art-e713e942071b4f0dacf1ac2cc3076fd6 |
| institution | Directory Open Access Journal |
| issn | 2251-6107 2783-4425 |
| language | English |
| last_indexed | 2024-04-10T16:40:33Z |
| publishDate | 2019-12-01 |
| publisher | Iran Telecom Research Center |
| record_format | Article |
| series | International Journal of Information and Communication Technology Research |
| spelling | doaj.art-e713e942071b4f0dacf1ac2cc3076fd62023-02-08T07:57:57ZengIran Telecom Research CenterInternational Journal of Information and Communication Technology Research2251-61072783-44252019-12-011144856Creating a Maximal Clique Graph to Improve Community Detection in SCoDA and OSLOM AlgorithmsSasan Sabour0Ali Moeini1 School of Engineering Science College of Engineering University of Tehran School of Engineering Science College of Engineering University of Tehran Community detection is one of the important topics regarding complex network study. There are many community detection algorithms such as Streaming Community Detection Algorithm (SCoDA) and Order Statistics Local Optimization Method (OSLOM). However, the performance of these algorithms, in overlap communities and communities with ambiguous structure, is problematic. In community detection algorithms achieving accurate results is a challenge. In this paper, we’ve proposed a method based on finding maximal cliques and generating the corresponding graph in order to use as an input to SCoDA and OSLOM algorithms. Synthetic non-overlap and overlap graphs and real graphs data are used in our experiments. F1score and NM1 score functions are utilized as our evaluation criteria. We have shown that the improved version of SCoDA demonstrated better results in comparison to the original SCoDA algorithm, and the improved version of OSLOM was also superior in performance when compared with the original OSLOM algorithm.http://ijict.itrc.ac.ir/article-1-447-en.htmlmaximal cliquemaximal clique graphoslomscodacommunity detectionnon-overlap communityoverlap community |
| spellingShingle | Sasan Sabour Ali Moeini Creating a Maximal Clique Graph to Improve Community Detection in SCoDA and OSLOM Algorithms International Journal of Information and Communication Technology Research maximal clique maximal clique graph oslom scoda community detection non-overlap community overlap community |
| title | Creating a Maximal Clique Graph to Improve Community Detection in SCoDA and OSLOM Algorithms |
| title_full | Creating a Maximal Clique Graph to Improve Community Detection in SCoDA and OSLOM Algorithms |
| title_fullStr | Creating a Maximal Clique Graph to Improve Community Detection in SCoDA and OSLOM Algorithms |
| title_full_unstemmed | Creating a Maximal Clique Graph to Improve Community Detection in SCoDA and OSLOM Algorithms |
| title_short | Creating a Maximal Clique Graph to Improve Community Detection in SCoDA and OSLOM Algorithms |
| title_sort | creating a maximal clique graph to improve community detection in scoda and oslom algorithms |
| topic | maximal clique maximal clique graph oslom scoda community detection non-overlap community overlap community |
| url | http://ijict.itrc.ac.ir/article-1-447-en.html |
| work_keys_str_mv | AT sasansabour creatingamaximalcliquegraphtoimprovecommunitydetectioninscodaandoslomalgorithms AT alimoeini creatingamaximalcliquegraphtoimprovecommunitydetectioninscodaandoslomalgorithms |