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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hu Le-wei Li Yu-sheng |
| Copyright Year | 2011 |
| Description | Author affiliation: Computer and Information Engineering Department, Wuhan Polytechnic University, Wuhan, China (Hu Le-wei; Li Yu-sheng) |
| Abstract | Association rules data mining on consumers condition in commercial websites is an important aspect of research in FP-Growth algorithm. In the general application of FP-Growth algorithm, the transaction data contain only the customers' purchase acts data, and neglect the data of acts which contain customers brow sing, selecting, evaluation, this phenomenon may lead to data distortion. For this reason, this text proposed a method which divides the customer acts data into browsing, evaluation, selection and purchasing four act data, and combines these data to the goods data, thus it can provides to commerce web site managers the results that more close to actual acts of the relevant rules. |
| Starting Page | 42 |
| Ending Page | 44 |
| File Size | 177914 |
| Page Count | 3 |
| File Format | |
| ISBN | 9781424486229 |
| e-ISBN | 9781424486250 |
| DOI | 10.1109/ITAIC.2011.6030146 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-08-20 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Computers FP-Growth Data structures Data Mining Transaction databases Association rules |
| Content Type | Text |
| Resource Type | Article |
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