Flow Provenance in Temporal Interaction Networks
Summary: Temporal interaction networks model entities exchanging quantities over time; this work traces flow origins at vertices (flow provenance). It formalizes flow-relay models for scenarios and offers provenance techniques to trace flow origins in dynamic networks. (summarized by gpt-5-nano on Feb 09 2026)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,861 | Efficient Provenance Storage | 2008 | SIGMOD | 0.00010287053 |
| 2,027 | Titian: Data Provenance Support in Spark | 2016 | VLDB | 9.7437067e-05 |
| 2,280 | SMOKE: Fine-grained Lineage at Interactive Speed | 2018 | VLDB | 9.1111033e-05 |
| 3,149 | Fine-Grained, Secure and Efficient Data Provenance on Blockchain Systems | 2019 | VLDB | 7.4741595e-05 |
| 5,086 | Improving Reproducibility of Data Science Pipelines through Transparent Provenance Capture | 2020 | VLDB | 5.7078462e-05 |
| 5,209 | Explaining Outputs in Modern Data Analytics | 2016 | VLDB | 5.629362e-05 |
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