This paper describes an approach to temporal pattern mining
using the concept of user dened temporal prototypes to dene the
nature of the trends of interests. The temporal patt...
Vassiliki Somaraki, Deborah Broadbent, Frans Coene...
This paper presents an LDA-style topic model that captures not only the low-dimensional structure of data, but also how the structure changes over time. Unlike other recent work t...
Algorithms that enable the process of automatically mining distinct topics in document collections have become increasingly important due to their applications in many fields and ...
We propose a generative model based on latent Dirichlet allocation for mining distinct topics in document collections by integrating the temporal ordering of documents into the ge...
Levent Bolelli, Seyda Ertekin, Ding Zhou, C. Lee G...
In this work we propose a novel approach to anomaly detection in streaming communication data. We first build a stochastic model for the system based on temporal communication pa...