Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14365/3563
Title: | Extending APAL to Detect Overlapping Communities in Weighted Networks | Authors: | Oğuz, Kaya Doluca, Osman |
Keywords: | overlapping community detection weighted networks Undirected graphs Benchmark suites Community detection algorithms High rate Normalized mutual information Overlapping communities Overlapping community detections Undirected graph Unweighted graphs Weighted networks Population dynamics |
Publisher: | Institute of Electrical and Electronics Engineers Inc. | Abstract: | APAL is an overlapping community detection algorithm that runs on undirected and unweighted graphs of any size. This study extends the algorithm to weighted networks by incorporating the average weight of the community to the evaluation process of the detected communities. Weighted-APAL (WAPAL) is tested with the established LFR benchmark suite against the weighted version of CPM. The resulting normalized mutual information scores show that it can detect weighted communities with a high rate of success. © 2022 IEEE. | Description: | 3rd International Informatics and Software Engineering Conference, IISEC 2022 -- 15 December 2022 through 16 December 2022 -- 185735 | URI: | https://doi.org/10.1109/IISEC56263.2022.9998238 https://hdl.handle.net/20.500.14365/3563 |
ISBN: | 9.78167E+12 |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
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