Discovery of Pairwise Ordinal Edit Rules

DOI

10.2991/asum.k.210827.015How to use a DOI?

Keywords

Data Quality, Edit rules, Ordinal data

Abstract

Edit rules are simple tuple-level constraints that concisely model which tuples are not permitted in a consistent relation. Previously, developed algorithms mostly assumed nominal data. This implies that ordinal data either had to be discarded or discretized according to expert knowledge. We can omit this by working with the ordinal data directly. In this paper we explore the discovery of low lift pairwise ordinal edit rules and propose an efficient algorithm employing several pruning strategies derived from the lift measure. Our experiments show that we can obtain a similar precision as nominal algorithms, while having an acceptable computational cost.

Copyright

© 2021, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Milan Peelman
AU  - Antoon Bronselaer
AU  - Guy De Tré
PY  - 2021
DA  - 2021/08/30
TI  - Discovery of Pairwise Ordinal Edit Rules
BT  - Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)
PB  - Atlantis Press
SP  - 109
EP  - 116
SN  - 2589-6644
UR  - https://doi.org/10.2991/asum.k.210827.015
DO  - 10.2991/asum.k.210827.015
ID  - Peelman2021
ER  -