Módszerek összehasonlítása
Tekintse át a kiválasztott módszereket egymás mellett; az eltérő sorok kiemelve jelennek meg.
| Súlyozott PageRank× | Szociális hálózatok elemzése× | |
|---|---|---|
| Tudományterület | Hálózatelemzés | Hálózatelemzés |
| Módszercsalád | Machine learning | Machine learning |
| Keletkezés éve≠ | 2004 | 1934 (sociometry); 1994 (modern formalization) |
| Megalkotó≠ | Xing, W. & Ghorbani, A. | Moreno, J.L.; formalized by Wasserman & Faust |
| Típus≠ | Centrality measure / ranking algorithm | Structural/relational analysis framework |
| Alapmű≠ | Xing, W., & Ghorbani, A. (2004). Weighted PageRank algorithm. Proceedings of the Second Annual Conference on Communication Networks and Services Research (CNSR '04), pp. 305–314. IEEE. DOI ↗ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 |
| Alternatív nevek | WPR, weighted page rank, edge-weighted PageRank, strength-based PageRank | SNA, network analysis, sociometric analysis, relational analysis |
| Kapcsolódó≠ | 6 | 5 |
| Összefoglaló≠ | Weighted PageRank extends the classic PageRank algorithm to networks where edges carry different strengths or frequencies, distributing importance proportionally to both incoming and outgoing edge weights rather than treating all links equally. This makes it substantially more informative than binary PageRank in any network where connection strength matters. | Social Network Analysis (SNA) is a structural method that maps and measures relationships and flows between people, groups, organizations, or other entities modeled as nodes connected by ties (edges). Rather than focusing on individual attributes, SNA reveals how the pattern of connections shapes behavior, influence, information flow, and outcomes within a system. |
| ScholarGateAdatkészlet ↗ |
|
|