%0 Computer Program %A Isupova, Olga %A Kuzin, Danil %A Mihaylova, Lyudmila %D 2018 %T Code for "Learning methods for dynamic topic modeling in automated behavior analysis" %U https://orda.shef.ac.uk/articles/software/Code_for_Learning_methods_for_dynamic_topic_modeling_in_automated_behavior_analysis_/5765556 %R 10.15131/shef.data.5765556.v1 %2 https://ndownloader.figshare.com/files/10159005 %K Video analytics %K Behavior analysis %K Learning dynamic models %K Unsupervised learning %K Expectation maximisation %K Variational Bayesian approach %K Computer Engineering %X
This is source code for the algorithms presented in the paper "Learning Methods for Dynamic Topic Modeling in Automated Behavior Analysis" by Olga Isupova, Danil Kuzin, Lyudmila Mihaylova. Published in IEEE Transactions on Neural Networks and Learning Systems, 2017. DOI: 10.1109/TNNLS.2017.2735364.

Two learning methods for the Markov Clustering Topic Model (MCTM) are developed - Expectation-Maximisation (EM) algorithm and Variational Bayes (VB) inference.
Implementation is done in Matlab.
%I The University of Sheffield