Discovery of Fuzzy Rare Association Rules from Large Transaction Databases

DOI

10.2991/emcm-16.2017.32How to use a DOI?

Keywords

Data mining; Association rules; Rare association rules; Fuzzy rare association rules

Abstract

Rare association rules is an association rule which has low support and high confidence. In recent years, the discovery of rare association rules has got quite a lot of attention, which has become a hot topic in data mining research. However, current discovery algorithms for rare association rules are built on the binary valued transaction databases, which can not deal with quantitative attributes. In this paper, we put forward a discovery algorithm for finding fuzzy rare association rules to handle quantitative attributes. Experiments on the synthetic data stream show that the proposed algorithm is efficient and scalable.

Copyright

© 2017, 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  - Weimin Ouyang
PY  - 2017/02
DA  - 2017/02
TI  - Discovery of Fuzzy Rare Association Rules from Large Transaction Databases
BT  - Proceedings of the 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)
PB  - Atlantis Press
SP  - 160
EP  - 165
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcm-16.2017.32
DO  - 10.2991/emcm-16.2017.32
ID  - Ouyang2017/02
ER  -