A simultaneous extraction of context and community from pervasive signals using nested Dirichlet process

Nguyen, T, Nguyen, V, Salim, F, Le, D and Phung, D 2017, 'A simultaneous extraction of context and community from pervasive signals using nested Dirichlet process', Pervasive and Mobile Computing, vol. 38, pp. 396-417.


Document type: Journal Article
Collection: Journal Articles

Title A simultaneous extraction of context and community from pervasive signals using nested Dirichlet process
Author(s) Nguyen, T
Nguyen, V
Salim, F
Le, D
Phung, D
Year 2017
Journal name Pervasive and Mobile Computing
Volume number 38
Start page 396
End page 417
Total pages 22
Publisher Elsevier
Abstract Understanding user contexts and group structures plays a central role in pervasive computing. These contexts and community structures are complex to mine from data collected in the wild due to the unprecedented growth of data, noise, uncertainties and complexities. Typical existing approaches would first extract the latent patterns to explain human dynamics or behaviors and then use them as a way to consistently formulate numerical representations for community detection, often via a clustering method. While being able to capture high-order and complex representations, these two steps are performed separately. More importantly, they face a fundamental difficulty in determining the correct number of latent patterns and communities. This paper presents an approach that seamlessly addresses these challenges to simultaneously discover latent patterns and communities in a unified Bayesian nonparametric framework. Our Simultaneous Extraction of Context and Community (SECC) model roots in the nested Dirichlet process theory which allows a nested structure to be built to summarize data at multiple levels. We demonstrate our framework on five datasets where the advantages of the proposed approach are validated.
Subject Ubiquitous Computing
Pattern Recognition and Data Mining
Keyword(s) Bayesian nonparametric
Community detection
Context discovery
Nested Dirichlet process
Pervasive signals
DOI - identifier 10.1016/j.pmcj.2016.08.019
Copyright notice © 2016 Elsevier B.V. All rights reserved
ISSN 1574-1192
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