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Authors: Tomasz Łukaszewski ; Joanna Józefowska and Agnieszka Ławrynowicz

Affiliation: Poznan University of Technology, Poland

Keyword(s): Ontologies, Imperfect Data, Naïve Bayesian Classifier.

Abstract: We propose a new concept to represent attribute values as an ontology that allows modeling different levels of abstraction. In this way more or less precise values may be used instead of missing or erroneous data. The goal is to use this representation in order to improve analysis of imperfect data. The proposed attribute value ontology (AVO) allows to upgrade the precision of information not only from positive observations but also from negative ones. We show how to classify a new example using a set of training examples described in the same or more precise way. Another advantage of the proposed approach is providing an efficient way to avoid the effect of overfitting.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Łukaszewski, T.; Józefowska, J. and Ławrynowicz, A. (2012). Attribute Value Ontology - Using Semantics in Data Mining. In Proceedings of the 14th International Conference on Enterprise Information Systems (ICEIS 2012) - Volume 1: SCOE; ISBN 978-989-8565-11-2; ISSN 2184-4992, SciTePress, pages 329-334. DOI: 10.5220/0004157003290334

@conference{scoe12,
author={Tomasz Łukaszewski. and Joanna Józefowska. and Agnieszka Ławrynowicz.},
title={Attribute Value Ontology - Using Semantics in Data Mining},
booktitle={Proceedings of the 14th International Conference on Enterprise Information Systems (ICEIS 2012) - Volume 1: SCOE},
year={2012},
pages={329-334},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004157003290334},
isbn={978-989-8565-11-2},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Enterprise Information Systems (ICEIS 2012) - Volume 1: SCOE
TI - Attribute Value Ontology - Using Semantics in Data Mining
SN - 978-989-8565-11-2
IS - 2184-4992
AU - Łukaszewski, T.
AU - Józefowska, J.
AU - Ławrynowicz, A.
PY - 2012
SP - 329
EP - 334
DO - 10.5220/0004157003290334
PB - SciTePress