Knowledge construction from time series data using a collaborative exploration system.

Thomas Guyet 1 Catherine Garbay 2 Michel Dojat 3, *
* Corresponding author
1 TIMC-IMAG-PRETA - Physiologie cardio-Respiratoire Expérimentale Théorique et Appliquée
TIMC-IMAG - Techniques de l'Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications, Grenoble - UMR 5525
Abstract : This paper deals with the exploration of biomedical multivariate time series to construct typical parameter evolution or scenarios. This task is known to be difficult: the temporal and multivariate nature of the data at hand and the context-sensitive aspect of data interpretation hamper the formulation of a priori knowledge about the kind of patterns that can be detected as well as their interrelations. This paper proposes a new way to tackle this problem based on a human-computer collaborative approach involving specific annotations. Three grounding principles, namely autonomy, adaptability and emergence, support the co-construction of successive abstraction levels for data interpretation. An agent-based design is proposed to support these principles. Preliminary results in a clinical context are presented to support our proposal. A comparison with two well-known time series exploration tools is furthermore performed.
Complete list of metadatas

Cited literature [37 references]  Display  Hide  Download

https://www.hal.inserm.fr/inserm-00381739
Contributor : Michel Dojat <>
Submitted on : Monday, July 6, 2009 - 5:59:33 PM
Last modification on : Tuesday, April 2, 2019 - 1:46:56 AM
Long-term archiving on : Saturday, November 26, 2016 - 8:26:12 AM

File

 Restricted access
To satisfy the distribution rights of the publisher, the document is embargoed until : jamais

Please log in to resquest access to the document

Identifiers

Citation

Thomas Guyet, Catherine Garbay, Michel Dojat. Knowledge construction from time series data using a collaborative exploration system.. Journal of Biomedical Informatics, Elsevier, 2007, 40 (6), pp.672-87. ⟨10.1016/j.jbi.2007.09.006⟩. ⟨inserm-00381739⟩

Share

Metrics

Record views

373