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A survey on ontologies for human behavior recognition

Authors:

Natalia Díaz Rodríguez,

M. P. Cuéllar,

Miguel Delgado Calvo-FloresAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 46, Issue 4

Article No.: 43, Pages 1 - 33

https://doi.org/10.1145/2523819

Published: 01 March 2014 Publication History

Abstract

Describing user activity plays an essential role in ambient intelligence. In this work, we review different methods for human activity recognition, classified as data-driven and knowledge-based techniques. We focus on context ontologies whose ultimate goal is the tracking of human behavior. After studying upper and domain ontologies, both useful for human activity representation and inference, we establish an evaluation criterion to assess the suitability of the different candidate ontologies for this purpose. As a result, any missing features, which are relevant for modeling daily human behaviors, are identified as future challenges.

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A survey on ontologies for human behavior recognition

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 46, Issue 4

April 2014

463 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/2597757

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Association for Computing Machinery

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Publication History

Published: 01 March 2014

Accepted: 01 August 2013

Revised: 01 March 2013

Received: 01 December 2012

Published in CSUR Volume 46, Issue 4

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