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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Min Dai Ya-Lou Huang |
| Copyright Year | 2005 |
| Description | Author affiliation: Dept. of Comput. Sci. & Technol., Nankai Univ., Tianjin, China (Min Dai; Ya-Lou Huang) |
| Abstract | Many existing association rules mining algorithms techniques often produce a large number of rules, which make it very difficult for the user to analyze them manually. The key problem is not with the large number of rules because if there are indeed many rules that exist in data, they should be discovered. The main problem is with our inability to organize and represent the rules in such a way that the user can easily comprehend them. This paper proposed a technique to intuitively organize the discovered association rules in a hierarchical fashion named general-specific (GS) pattern. With this organization, the user can view the association rules at different level of details. The technique first finds a subset of the association rules called the most-general rules set (MGRS) to give the user a general relationship or a big picture of the original rules set. Then, the user can selectively view more-specific rules below a general rule that are interesting to him/her. Experiment results and practical applications show that the technique is both intuitive and effective. |
| Sponsorship | IEEE Syst., Man and Cybernetics Tech. Comm. on Cybernetics, Hong Kong Polytechnic Univ. Hebei Univ. South China Univ. Chongqing Univ. Sun Yat-sen Univ. Harbin Inst. of Technol. and Int. Univ. in Germany |
| Starting Page | 2206 |
| Ending Page | 2211 |
| File Size | 354626 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780390911 |
| DOI | 10.1109/ICMLC.2005.1527311 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2005-08-18 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Organizing Association rules Data mining Computer science Databases Electronic mail Pattern analysis Algorithm design and analysis Bellows Pattern recognition More-Specific Rules Data Mining Organization More-General Rules |
| Content Type | Text |
| Resource Type | Article |
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