loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 52.15.170.196

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

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

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic