Modeling Events with Cascades of Poisson Processes

Details Modeling Events with Cascades of Poisson Processes Modeling Events with Cascades of Poisson Processes

2012-03-15

arxiv.org/abs/1203.3516v1

Computer Science

Learning

Appears in Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (UAI2010)

Scientific paper

We present a probabilistic model of events in continuous time in which each event triggers a Poisson process of successor events. The ensemble of observed events is thereby modeled as a superposition of Poisson processes. Efficient inference is feasible under this model with an EM algorithm. Moreover, the EM algorithm can be implemented as a distributed algorithm, permitting the model to be applied to very large datasets. We apply these techniques to the modeling of Twitter messages and the revision history of Wikipedia.

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