方法证据记录
Dynamic PageRank
Dynamic PageRank extends the classic PageRank algorithm to networks whose edges carry timestamps, assigning importance scores that evolve over time. By discounting older links and emphasising recent connections, it identifies nodes that are influential at specific moments rather than across the entire network history, making it well-suited for web archives, citation streams, social media cascades, and any domain where link recency matters.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Dynamic PageRank (Temporal Extension of the PageRank Algorithm)
分类方法记录 · ml-model / network-analysis
- 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), Lecture Notes in Computer Science, 9853, 674–689. Springer. · DOI 10.1007/978-3-319-46227-1_42
- Berberich, K., Vazirgiannis, M., & Weikum, G. (2007). Time-aware authority ranking. Internet Mathematics, 3(4), 407–429. · URL
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