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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Altincay, H. |
| Copyright Year | 2013 |
| Description | Author affiliation: Bilgisayar Muhendisligi Bolumu, Dogu Akdeniz Univ., Gazimağusa, Turkey (Altincay, H.) |
| Abstract | The use of linear regression residual for binary text categorization is studied. The main idea is to predict the given test vector using its k nearest neighbors in both positive and negative classes. The predicted vectors are the projections of the test vector onto the subspaces of different classes. The differences between the test vector and the projections are known as the residual vectors. The magnitudes of these vectors show the effectiveness of the neighbors in different classes to represent the test vector. The residuals obtained from both positive and negative classes are cancatenated with the document vectors computed using bag of words approach. Experimental results on three widely used datasets have shown that residual vectors provide improved document representation. |
| Sponsorship | IEEE Turkey Sect. SP Chapter |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 334066 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467355629 |
| e-ISBN | 9781467355636 |
| e-ISBN | 9781467355612 |
| DOI | 10.1109/SIU.2013.6531161 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-04-24 |
| Publisher Place | Turkey |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Radio frequency Support vector machines Face recognition Text categorization Linear regression document representation linear regression text categorization Vectors Marine vehicles residual vector |
| Content Type | Text |
| Resource Type | Article |
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