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Authors: Fabio Fassetti and Fabrizio Angiulli

Affiliation: DEIS, University of Calabria, Italy

ISBN: 978-989-674-021-4

Keyword(s): Data mining, Example-based outlier detection, Genetic algorithms.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Data Manipulation ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: In this work an example-based outlier detection method exploiting both positive (that is, outlier) and negative (that is, inlier) examples in order to guide the search for anomalies in an unlabelled data set, is introduced. The key idea of the method is to find the subspace where positive examples mostly exhibit their outlierness while at the same time negative examples mostly exhibit their inlierness. The degree to which an example is an outlier is measured by means of well-known unsupervised outlier scores evaluated on the collection of unlabelled data. A subspace discovery algorithm is designed, which searches for the most discriminating subspace. Experimental results show that the method is able to detect a near optimal solution, and that the method is promising from the point of view of the knowledge mined.

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Paper citation in several formats:
Fassetti F.; Angiulli F. and (2010). FINDING DISTANCE-BASED OUTLIERS IN SUBSPACES THROUGH BOTH POSITIVE AND NEGATIVE EXAMPLES.In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-674-021-4, pages 5-10. DOI: 10.5220/0002699600050010

@conference{icaart10,
author={Fabio Fassetti and Fabrizio Angiulli},
title={FINDING DISTANCE-BASED OUTLIERS IN SUBSPACES THROUGH BOTH POSITIVE AND NEGATIVE EXAMPLES},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2010},
pages={5-10},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002699600050010},
isbn={978-989-674-021-4},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - FINDING DISTANCE-BASED OUTLIERS IN SUBSPACES THROUGH BOTH POSITIVE AND NEGATIVE EXAMPLES
SN - 978-989-674-021-4
AU - Fassetti, F.
AU - Angiulli, F.
PY - 2010
SP - 5
EP - 10
DO - 10.5220/0002699600050010

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