Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Outlier detection by logic programming

Outlier detection by logic programming Outlier Detection by Logic Programming FABRIZIO ANGIULLI, GIANLUIGI GRECO, and LUIGI PALOPOLI University of Calabria, Italy The development of effective knowledge discovery techniques has become a very active research area in recent years due to the important impact it has had in several relevant application domains. One interesting task therein is that of singling out anomalous individuals from a given population, for example, to detect rare events in time-series analysis settings, or to identify objects whose behavior is deviant w.r.t. a codi ed standard set of rules. Such exceptional individuals are usually referred to as outliers in the literature. In this article, the concept of outlier is formally stated in the context of knowledge-based systems, by generalizing that originally proposed in Angiulli et al. [2003] in the context of default theories. The chosen formal framework here is that of logic programming, wherein potential applications of techniques for outlier detection are thoroughly discussed. The proposed formalization is a novel one and helps to shed light on the nature of outliers occurring in logic bases. Also the exploitation of minimality criteria in outlier detection is illustrated. The computational complexity of outlier detection problems arising in this novel setting is also http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Computational Logic (TOCL) Association for Computing Machinery

Outlier detection by logic programming

Download PDF
56 pages

Loading next page...
 
/lp/association-for-computing-machinery/outlier-detection-by-logic-programming-sYJUEbsGO3

References (107)

Publisher
Association for Computing Machinery
Copyright
Copyright © 2007 by ACM Inc.
ISSN
1529-3785
DOI
10.1145/1297658.1297665
Publisher site
See Article on Publisher Site

Abstract

Outlier Detection by Logic Programming FABRIZIO ANGIULLI, GIANLUIGI GRECO, and LUIGI PALOPOLI University of Calabria, Italy The development of effective knowledge discovery techniques has become a very active research area in recent years due to the important impact it has had in several relevant application domains. One interesting task therein is that of singling out anomalous individuals from a given population, for example, to detect rare events in time-series analysis settings, or to identify objects whose behavior is deviant w.r.t. a codi ed standard set of rules. Such exceptional individuals are usually referred to as outliers in the literature. In this article, the concept of outlier is formally stated in the context of knowledge-based systems, by generalizing that originally proposed in Angiulli et al. [2003] in the context of default theories. The chosen formal framework here is that of logic programming, wherein potential applications of techniques for outlier detection are thoroughly discussed. The proposed formalization is a novel one and helps to shed light on the nature of outliers occurring in logic bases. Also the exploitation of minimality criteria in outlier detection is illustrated. The computational complexity of outlier detection problems arising in this novel setting is also

Journal

ACM Transactions on Computational Logic (TOCL) – Association for Computing Machinery

Published: Dec 1, 2007

There are no references for this article.