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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Watanabe, T. Takahashi, H. |
| Copyright Year | 2006 |
| Description | Author affiliation: Osaka Electro-Commun. Univ., Osaka (Watanabe, T.) |
| Abstract | In order to develop a data mining system for huge database mainly composed of numerical attributes, there exists necessary process to decide valid quantization of the numerical attributes. Though the clustering algorithm can provide useful information for the quantization problem, it is difficult to formulate appropriate clusters for rule extraction in terms of cluster size and shape. In this paper, we propose a new method of quantitative association rule extraction that can quantize the attribute by applying clustering algorithm and extract rules simultaneously. From the results of numerical experiments using benchmark data, the method is found to be promised for actual applications. |
| Starting Page | 2652 |
| Ending Page | 2657 |
| File Size | 2415776 |
| Page Count | 6 |
| File Format | |
| ISBN | 1424400996 |
| DOI | 10.1109/ICSMC.2006.385264 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-10-08 |
| Publisher Place | Taiwan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Clustering algorithms Association rules Data mining Fuzzy sets Transaction databases Partitioning algorithms Quantization Humans Itemsets Cybernetics |
| Content Type | Text |
| Resource Type | Article |
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