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Authors: Marjan Alirezaie 1 and Amy Loutfi 2

Affiliations: 1 Örebro University, Sweden ; 2 Orebro University, Sweden

Keyword(s): Sensor, Semantic Perception, Abduction, Knowledge Acquisition.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Collaboration and e-Services ; Data Engineering ; e-Business ; Enterprise Information Systems ; Information Integration ; Integration/Interoperability ; Knowledge Acquisition ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Ontologies and the Semantic Web ; Ontology Sharing and Reuse ; Symbolic Systems

Abstract: Fast growing structured knowledge in machine processable formats such as RDF/OWL provides the opportunity of having automatic annotation for stream data in order to extract meaningful information. In this work, we propose a system architecture to model the process of stream data annotation in an automatized fashion using public repositories of knowledge. We employ abductive reasoning which is capable of retrieving the best explanations for observations given incomplete knowledge. In order to evaluate the effectiveness of the framework, we use multivariate data coming from medical sensors observing a patient in ICU (Intensive Care Unit) suffering from several diseases as the ground truth against which the eventual explanations (annotations) of the reasoner are compared.

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Paper citation in several formats:
Alirezaie, M. and Loutfi, A. (2013). Automatic Annotation of Sensor Data Streams using Abductive Reasoning. In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (IC3K 2013) - KEOD; ISBN 978-989-8565-81-5; ISSN 2184-3228, SciTePress, pages 345-354. DOI: 10.5220/0004623403450354

@conference{keod13,
author={Marjan Alirezaie. and Amy Loutfi.},
title={Automatic Annotation of Sensor Data Streams using Abductive Reasoning},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development (IC3K 2013) - KEOD},
year={2013},
pages={345-354},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004623403450354},
isbn={978-989-8565-81-5},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development (IC3K 2013) - KEOD
TI - Automatic Annotation of Sensor Data Streams using Abductive Reasoning
SN - 978-989-8565-81-5
IS - 2184-3228
AU - Alirezaie, M.
AU - Loutfi, A.
PY - 2013
SP - 345
EP - 354
DO - 10.5220/0004623403450354
PB - SciTePress