2015
Online time-dependent clustering using probabilistic topic models
ICASSP 2015accepted
We introduce an online, time-dependent clustering algorithm that employs a dynamic probabilistic topic model. The proposed algorithm can handle data that evolves over time and strives to capture the evolution of clusters in the dataset. It addresses the case where the entire dataset is not available…