পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| নির্দেশিত মডুলারিটি বিশ্লেষণ× | মডিউলারিটি বিশ্লেষণ× | |
|---|---|---|
| ক্ষেত্র | নেটওয়ার্ক বিশ্লেষণ | নেটওয়ার্ক বিশ্লেষণ |
| পরিবার | Machine learning | Machine learning |
| উদ্ভবের বছর≠ | 2008 | 2004 |
| প্রবর্তক≠ | Leicht, E. A. & Newman, M. E. J. | Newman, M. E. J. & Girvan, M. |
| ধরন | Community detection / graph partitioning | Community detection / graph partitioning |
| মৌলিক উৎস≠ | Leicht, E. A., & Newman, M. E. J. (2008). Community structure in directed networks. Physical Review Letters, 100(11), 118703. DOI ↗ | Newman, M. E. J., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69(2), 026113. DOI ↗ |
| অপর নাম | directed community detection via modularity, directed Q-modularity, digraph modularity optimization, Leicht-Newman modularity | Q-modularity, community structure detection, network modularity optimization, graph partitioning by modularity |
| সম্পর্কিত | 5 | 5 |
| সারসংক্ষেপ≠ | Directed modularity analysis extends the classic Newman-Girvan modularity framework to directed graphs, where edges carry a source and a destination. Formalized by Leicht and Newman in 2008, it partitions nodes into communities by maximizing a modularity score that accounts for each node's separate in-degree and out-degree in the null model, making it the standard approach for community detection in citation networks, information flows, and other asymmetric relational data. | Modularity analysis is a network science method, formalized by Newman and Girvan in 2004, that detects community structure in graphs by measuring whether edges are more concentrated within groups than expected by chance. Its scalar quality index Q guides algorithms that partition nodes into cohesive clusters, making it the most widely adopted framework for community detection in social, biological, and technological networks. |
| ScholarGateডেটাসেট ↗ |
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