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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiaoyuan Zhu Yongquan Yu Xueyan Guo |
| Copyright Year | 2009 |
| Abstract | When traditional genetic algorithm is applied in mining association rules, it would get into local prematurity and becomes slow-footed in convergence.The paper brings forward that evolution strategy's excellence is applied in genetic algorithm’s evolutional process. Then optimized genetic algorithm is used for mining association rules. In order to test the validity of the arithmetic, this paper presents a example of data mining about finance service. Research result indicates that the arithmetic can enhance search speed and data accuracy. Consequently it can effectively drive farther development of data mining. |
| Starting Page | 848 |
| Ending Page | 852 |
| File Size | 472712 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424435814 |
| DOI | 10.1109/ETCS.2009.192 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-03-07 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Data analysis Data Mining Data mining Association rules Genetic algorithms Convergence Evolution Strategy Forward contracts Genetic Agorithm Computer science education Artificial intelligence Arithmetic |
| Content Type | Text |
| Resource Type | Article |
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