Automatic Annotation of Sensor Data Streams using Abductive Reasoning

Marjan Alirezaie, Amy Loutfi


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 Harvard Style

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 - Volume 1: KEOD, (IC3K 2013) ISBN 978-989-8565-81-5, pages 345-354. DOI: 10.5220/0004623403450354

in Bibtex Style

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 - Volume 1: KEOD, (IC3K 2013)},

in EndNote Style

JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2013)
TI - Automatic Annotation of Sensor Data Streams using Abductive Reasoning
SN - 978-989-8565-81-5
AU - Alirezaie M.
AU - Loutfi A.
PY - 2013
SP - 345
EP - 354
DO - 10.5220/0004623403450354