Activity date estimation in timestamped interaction networks

2013/10/18 by Fabrice Rossi, Pierre Latouche, Rossi, Fabrice +1
Computer Science · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Social and Information Networks (cs.SI) #Statistics Theory (math.ST) #cs.SI #math.ST #stat.TH

paper · pdf · doi:10.48550/arxiv.1310.4914

21-th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2013), Bruges : Belgium (2013)

arxiv created 2013/10/18 · arxiv updated 2013/10/21

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

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