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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jun Hu Zhitang Li Zhengbing Hu Dezhong Yao Junfeng Yu |
| Copyright Year | 2008 |
| Description | Author affiliation: Huazhong Univ. of Sci. & Technol., Wuhan (Jun Hu; Zhitang Li; Zhengbing Hu; Dezhong Yao; Junfeng Yu) |
| Abstract | The paper proposes the use of the complex-valued neural network to detect spam. The main contributions of this work are two-fold. First, we present a new model based on the CVNN for classifying personal E-mails. We changed the input of the email into 2-dimensional vector. The complex-valued neural network is superior for handling 2-dimensional vector data stream, because the input of the complex-valued neural network has real part and imaginary part. Second, the behavior-based characteristics are extracted as most important features of the E-mail. The results reveal that the proposed technology is reliable, efficient and scalable. |
| Starting Page | 166 |
| Ending Page | 169 |
| File Size | 238839 |
| Page Count | 4 |
| File Format | |
| ISBN | 9780769533346 |
| DOI | 10.1109/WGEC.2008.72 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-09-25 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Strontium Filtering Neurons Unsolicited electronic mail Artificial neural networks Electronic mail Servers spam CVNN |
| Content Type | Text |
| Resource Type | Article |
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