Mining Weighted Rare Association Rules Using Sliding Window over Data Streams

DOI

10.2991/cset-16.2016.28How to use a DOI?

Keywords

Rare association rules, weighted rare association rules, data streams, sliding window

Abstract

Rare association rules mining is an association rule which has low support and high confidence. In recent years, the problem of mining rare association rules has got quite a lot of attention, which has become a hot topic in data mining research. However, most of the research on mining rare association rules are confined to the static database environment, and treat each item with the same significance although different items may have different significance. In this paper, we propose an algorithm for mining weighted rare association rules over data streams with a sliding window. Experiments on the synthetic data stream show that the proposed algorithm is efficient and scalable.

Copyright

© 2016, 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  - 2016/08
DA  - 2016/08
TI  - Mining Weighted Rare Association Rules Using Sliding Window over Data Streams
BT  - Proceedings of the 2016 International Conference on Computer Science and Electronic Technology
PB  - Atlantis Press
SP  - 116
EP  - 119
SN  - 2352-538X
UR  - https://doi.org/10.2991/cset-16.2016.28
DO  - 10.2991/cset-16.2016.28
ID  - Ouyang2016/08
ER  -