Evolutionary Active Constrained Clustering for Obstructive Sleep Apnea Analysis View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-11-07

AUTHORS

Son T. Mai, Sihem Amer-Yahia, Sébastien Bailly, Jean-Louis Pépin, Ahlame Douzal Chouakria, Ky T. Nguyen, Anh-Duong Nguyen

ABSTRACT

We introduce a novel interactive framework to handle both instance-level and temporal smoothness constraints for clustering large longitudinal data and for tracking the cluster evolutions over time. It consists of a constrained clustering algorithm, called CVQE+, which optimizes the clustering quality, constraint violation and the historical cost between consecutive data snapshots. At the center of our framework is a simple yet effective active learning technique, named Border, for iteratively selecting the most informative pairs of objects to query users about, and updating the clustering with new constraints. Those constraints are then propagated inside each data snapshot and between snapshots via two schemes, called constraint inheritance and constraint propagation, to further enhance the results. Moreover, a historical constraint is enforced between consecutive snapshots to ensure the consistency of results among them. Experiments show better or comparable clustering results than state-of-the-art techniques as well as high scalability for large datasets. Finally, we apply our algorithm for clustering phenotypes in patients with Obstructive Sleep Apnea as well as for tracking how these clusters evolve over time. More... »

PAGES

359-378

References to SciGraph publications

  • 2014-06-24. Temporal disease trajectories condensed from population-wide registry data covering 6.2 million patients in NATURE COMMUNICATIONS
  • 2011-03-16. Effective semi-supervised document clustering via active learning with instance-level constraints in KNOWLEDGE AND INFORMATION SYSTEMS
  • 2018-05-13. Scalable Active Constrained Clustering for Temporal Data in DATABASE SYSTEMS FOR ADVANCED APPLICATIONS
  • 2015-06-25. Obstructive sleep apnoea syndrome in NATURE REVIEWS DISEASE PRIMERS
  • 2007-01-01. K-Means with Large and Noisy Constraint Sets in MACHINE LEARNING: ECML 2007
  • 2012-11-21. Multi-view constrained clustering with an incomplete mapping between views in KNOWLEDGE AND INFORMATION SYSTEMS
  • 2018-04-10. Anytime parallel density-based clustering in DATA MINING AND KNOWLEDGE DISCOVERY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s41019-018-0080-6

    DOI

    http://dx.doi.org/10.1007/s41019-018-0080-6

    DIMENSIONS

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