Please use this identifier to cite or link to this item:
https://ptsldigital.ukm.my/jspui/handle/123456789/395132| Title: | Arabic part-of-speech tagger based support vectors machines |
| Authors: | Jabar Hassan Yousif Tengku Mohd Tengku Sembok |
| Conference Name: | International Symposium on Information Technology |
| Keywords: | Arabic part-of-speech Vectors machines |
| Conference Date: | 26/08/2008 |
| Conference Location: | Kuala Lumpur Convention Centre |
| Abstract: | Support Vector Machines (SVMs) and related kernel methods have become widely known tools for text mining tasks such as classification and regression. The Arabic part of speech (POS) based support vectors machine is designed and implemented. The NeuroSolutions software is used to adopt and learn the proposed tagger. The Radial basis functions (RBFs) is used as a linear function approximator. The experiments has give an evinced that the SVMS tagger is accurate of (99.99%), has low processing time, and use a little a mount of data at training phase . |
| Pages: | 7 |
| Call Number: | T58.5.C634 2008 kat sem j.3 |
| Publisher: | Institute of Electrical and Electronics Engineers (IEEE),Piscataway, US |
| Appears in Collections: | Seminar Papers/ Proceedings / Kertas Kerja Seminar/ Prosiding |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.