Efficient Updating of Node Importance in Dynamic Real-Life Networks
| Autor: | Joost Berkhout, Bernd Heidergott |
|---|---|
| Přispěvatelé: | Centrum Wiskunde & Informatica, Amsterdam (CWI), The Netherlands, Amsterdam Business Research Institute, Econometrics and Operations Research, Tinbergen Institute |
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Theoretical computer science Computer science Markov models 02 engineering and technology Markov model 01 natural sciences 010104 statistics & probability 020901 industrial engineering & automation Ergodic theory 0101 mathematics Resolvent Social network Markov chain business.industry Node (networking) Random walk Ergodic projector Markov multi-chain Ranking nodes Control and Systems Engineering The Internet Networks SDG 12 - Responsible Consumption and Production business |
| Zdroj: | IFAC-PapersOnLine, 51(7), 64-69 Berkhout, J & Heidergott, B F 2018, ' Efficient Updating of Node Importance in Dynamic Real-Life Networks ', IFAC-PapersOnLine, vol. 51, no. 7, pp. 64-69 . https://doi.org/10.1016/j.ifacol.2018.06.280 IFAC-PapersOnLine, 51(7), 64-69. IFAC Secretariat |
| ISSN: | 2405-8963 |
| DOI: | 10.1016/j.ifacol.2018.06.280 |
| Popis: | The analysis of real-life networks, such as the internet, biometrical networks, and social networks, is challenged by the constantly changing structure of these networks. Typically, such networks consist of multiple weakly connected subcomponents and efficiently updating the importance of network nodes, as captured by the ergodic projector of a random walk on these networks, is a challenging task. In this paper, new approximations are introduced that allow to efficiently update the ergodic projector of Markov multi-chains. Properties such as convergence and error bounds for approximations are established. The numerical applicability is illustrated with a real-life social network example. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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