Mining Weighted Rare Association Rules Using Sliding Window over Data Streams
Authors
Weimin Ouyang
Corresponding Author
Weimin Ouyang
Available Online August 2016.
- DOI
- https://doi.org/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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Weimin Ouyang PY - 2016/08 DA - 2016/08 TI - Mining Weighted Rare Association Rules Using Sliding Window over Data Streams BT - 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 - https://doi.org/10.2991/cset-16.2016.28 ID - Ouyang2016/08 ER -