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PageRank ya Muda (Temporal PageRank)

PageRank ya Muda inapanua algoriti ya kawaida ya PageRank kwa mitandao inayoendelea kubadilika kwa wakati kwa kujumuisha usasa na mpangilio wa mwingiliano. Njia (edges) hupewa uzito kwa kutumia kitendakazi cha kuoza (decay function) ili mawasiliano ya hivi karibuni yachangie zaidi kwenye alama ya nodi kuliko yale ya zamani. Matokeo yake ni orodha ya umuhimu inayobadilika-badilika ambayo inanasua nani ana ushawishi kwa sasa, badala ya historia nzima ya mtandao.

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Method map

The neighbourhood of related methods — select a node to explore.

Vyanzo

  1. Rozenshtein, P. & Gionis, A. (2016). Temporal PageRank. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Part II, LNCS 9852, pp. 674–689. Springer. DOI: 10.1007/978-3-319-46227-1_42
  2. Lerman, K. & Ghosh, R. (2010). Information Contagion: An Empirical Study of the Spread of News on Digg and Twitter Social Networks. In Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media (ICWSM), pp. 90–97. AAAI Press. link

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Temporal PageRank (Time-Aware Node Importance Ranking in Temporal Networks). ScholarGate. https://scholargate.app/sw/network-analysis/temporal-pagerank

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

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Imerejelewa na

ScholarGateTemporal PageRank (Temporal PageRank (Time-Aware Node Importance Ranking in Temporal Networks)). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/network-analysis/temporal-pagerank · Seti ya data: https://doi.org/10.5281/zenodo.20539026