Fuzzy Meta-Association Rules

DOI

10.2991/ifsa-eusflat-15.2015.37How to use a DOI?

Keywords

Fuzzy association rules, metaassociation rules, higher order mining.

Abstract

Association rules is a useful tool to extract new information from raw data expressed in a comprehensive way for decision makers. However, in some applications raw data might not be available for several reasons. First, stream data are only temporarily available for their processing or if it is stored, only summaries or representations of the extracted knowledge are kept. Second, under some circumstances primary data cannot be disclosed due to privacy or legal restrictions. In the light of these observations we propose fuzzy meta-association rules for mining association rules over already discovered rules in a set of databases sharing common information. We compare this proposal with a previous one using crisp meta-rules showing that fuzzy metaassociation rules discover interesting knowledge obtaining a more manageable set of rules for human inspection and allowing the use of fuzzy items to express additional knowledge about the original databases.

Copyright

© 2015, 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  - M.Dolores Ruiz
AU  - Juan Gómez-Romero
AU  - M. José Martin-Bautista
AU  - M. Amparo Vila
AU  - Miguel Delgado
PY  - 2015/06
DA  - 2015/06
TI  - Fuzzy Meta-Association Rules
BT  - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 247
EP  - 254
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.37
DO  - 10.2991/ifsa-eusflat-15.2015.37
ID  - Ruiz2015/06
ER  -