Skip to Main content Skip to Navigation
Conference papers

Activity date estimation in timestamped interaction networks

Abstract : We propose in this paper a new generative model for graphs that uses a latent space approach to explain timestamped interactions. The model is designed to provide global estimates of activity dates in historical networks where only the interaction dates between agents are known with reasonable precision. Experimental results show that the model provides better results than local averages in dense enough networks
Complete list of metadatas

Cited literature [5 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-00825967
Contributor : Fabrice Rossi <>
Submitted on : Thursday, October 17, 2013 - 9:35:05 PM
Last modification on : Sunday, January 19, 2020 - 6:38:32 PM
Long-term archiving on: : Friday, April 7, 2017 - 12:56:16 PM

Files

rossilatouche2013activity-date...
Files produced by the author(s)

Identifiers

  • HAL Id : hal-00825967, version 2
  • ARXIV : 1310.4914

Collections

Citation

Fabrice Rossi, Pierre Latouche. Activity date estimation in timestamped interaction networks. 21-th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2013), Apr 2013, Bruges, Belgium. pp.113-118. ⟨hal-00825967v2⟩

Share

Metrics

Record views

329

Files downloads

84