Combining structural and dynamic information to predict activity in link streams

Author:

Arnoux Thibaud1,Tabourier Lionel1,Latapy Matthieu1

Affiliation:

1. Sorbonne Universités, CNRS, Jussieu, Paris

Funder

ANR

Ile-de-France pro- gram FUI21

European Commission

PIA - Usages, services et contenus innovants

Publisher

ACM

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. PIDKG: Propagating Interaction Influence on the Dynamic Knowledge Graph for Recommendation;ACM Transactions on the Web;2024-01-08

2. TeGraph: A Novel General-Purpose Temporal Graph Computing Engine;2022 IEEE 38th International Conference on Data Engineering (ICDE);2022-05

3. A Novel Deep Link Prediction Model for Peer-to-Peer Dynamic Task Collaboration Networks;Peer-to-Peer Networking and Applications;2022-04-19

4. Highly Liquid Temporal Interaction Graph Embeddings;Proceedings of the Web Conference 2021;2021-04-19

5. Mining Stable Communities in Temporal Networks by Density-based Clustering;IEEE Transactions on Big Data;2020

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