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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