• Corpus ID: 63087632

# Discovering Archetypes to Interpret Evolution of Individual Behavior

@article{Narang2019DiscoveringAT,
title={Discovering Archetypes to Interpret Evolution of Individual Behavior},
author={Kanika Narang and Austin Chung and H. Sundaram and Snigdha Chaturvedi},
journal={ArXiv},
year={2019},
volume={abs/1902.05567}
}
• Published 14 February 2019
• Computer Science
• ArXiv
In this paper, we aim to discover archetypical patterns of individual evolution in large social networks. In our work, an archetype comprises of \emph{progressive stages} of distinct behavior. We introduce a novel Gaussian Hidden Markov Model (G-HMM) Cluster to identify archetypes of evolutionary patterns. G-HMMs allow for: near limitless behavioral variation; imposing constraints on how individuals can evolve; different evolutionary rates; and are parsimonious. Our experiments with Academic…
3 Citations

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