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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Shengjun Xue Hongtao Wang Tan Ran |
| Copyright Year | 2008 |
| Description | Author affiliation: Sch. of Comput. Sci. & Technol., Wuhan Univ. of Technol., Wuhan (Hongtao Wang; Tan Ran) || Comput. & Software Inst., Nanjing Univ. of Inf. Sci. & Technol., Nanjing (Shengjun Xue) |
| Abstract | For the complex data of multilevel and large volume distributed in different regions, how to seek and find both be interested and useful information is what scientists are devoted to. Existing efficient method of research is an association rule mining of distributed database system. This paper introduced the distributed association rule mining algorithm. By analyzing the Aproiri algorithm, we have proposed Fast Distributed Mining of Association Rule algorithm and Similarity model. The test results show it can effectively improve the mining accuracy rate. |
| Starting Page | 411 |
| Ending Page | 414 |
| File Size | 287809 |
| Page Count | 4 |
| File Format | |
| ISBN | 9780769533360 |
| DOI | 10.1109/CSSE.2008.1359 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-12-12 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | association rule Software algorithms data mining Distributed decision making Transaction databases Data mining Association rules Computer science Itemsets Distributed databases Database systems similarit Software engineering algorithm data resource heterogeneous |
| Content Type | Text |
| Resource Type | Article |
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