A community detection approach based on network representation learning for repository mining
Authors:
- Marco De LucaMLMarco De Luca
- Anna Rita FasolinoAFAnna Rita Fasolino
- Antonino FerraroAntonino Ferraro
- Vincenzo MoscatoVMVincenzo Moscato
- Giancarlo SperlíGiancarlo Sperlí
- Porfirio TramontanaPorfirio Tramontana
- 8 June 2023
- journal article
- research article
- Published by Elsevier in Expert Systems with Applications
- Vol. 231
Abstract
No abstract availableKeywords
This publication has 16 references indexed in Scilit:
- Community detection in software ecosystem by comprehensively evaluating developer cooperation intensityInformation and Software Technology, 2021
- A systematic mapping study of developer social network researchJournal of Systems and Software, 2021
- An automated approach to assess the similarity of GitHub repositoriesSoftware Quality Journal, 2020
- A Comprehensive Survey of Graph Embedding: Problems, Techniques, and ApplicationsIEEE Transactions on Knowledge and Data Engineering, 2018
- A review of clustering techniques and developmentsNeurocomputing, 2017
- Metrics for Community AnalysisACM Computing Surveys, 2017
- Equivalence between modularity optimization and maximum likelihood methods for community detectionPhysical Review E, 2016
- Influence analysis of Github repositoriesSpringerPlus, 2016
- Representation Learning: A Review and New PerspectivesIEEE Transactions on Pattern Analysis and Machine Intelligence, 2013
- Selection of K in K-means clusteringProceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2005