পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| মধ্যস্থতা কেন্দ্রিকতা× | মডিউলারিটি বিশ্লেষণ× | |
|---|---|---|
| ক্ষেত্র | নেটওয়ার্ক বিশ্লেষণ | নেটওয়ার্ক বিশ্লেষণ |
| পরিবার | Machine learning | Machine learning |
| উদ্ভবের বছর≠ | 1977 | 2004 |
| প্রবর্তক≠ | Freeman, L. C. | Newman, M. E. J. & Girvan, M. |
| ধরন≠ | Centrality measure | Community detection / graph partitioning |
| মৌলিক উৎস≠ | Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41. DOI ↗ | Newman, M. E. J., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69(2), 026113. DOI ↗ |
| অপর নাম | Freeman betweenness, BC, geodesic betweenness, shortest-path betweenness | Q-modularity, community structure detection, network modularity optimization, graph partitioning by modularity |
| সম্পর্কিত≠ | 6 | 5 |
| সারসংক্ষেপ≠ | Betweenness centrality, formalized by Linton C. Freeman in 1977, measures how often a node lies on the shortest path connecting every other pair of nodes in a network. High-betweenness nodes act as bridges or brokers: removing them fragments the network into disconnected components more severely than removing any other nodes. | 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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