Due to the wide proliferation of the Internet and telecommunication, huge amount of information has been produced as digital data format. It is impossible to classify this information with one's own hand one by one in many realistic problems, so that the research on automatic text classification has been grown. Machine learning technologies have applied in text classification. However, the traditional statistic machine learning technologies require large number of labeled training examples to learn accurately. To obtain enough training examples, we have to label on these huge training examples by hand. This paper presents a supervised learning algorithm based on support vector machine (SVM) to classify text documents more accurately by using unlabeled documents to augment available labeled training examples. Experimental results indicate that the classification with unlabeled examples using SVM is superior to the conventional classification,with labeled examples.
|Title of host publication||ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing|
|Subtitle of host publication||Computational Intelligence for the E-Age|
|Editors||Jagath C. Rajapakse, Soo-Young Lee, Lipo Wang, Kunihiko Fukushima, Xin Yao|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||5|
|ISBN (Electronic)||9810475241, 9789810475246|
|Publication status||Published - 2002|
|Event||9th International Conference on Neural Information Processing, ICONIP 2002 - Singapore, Singapore|
Duration: 2002 Nov 18 → 2002 Nov 22
|Name||ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age|
|Other||9th International Conference on Neural Information Processing, ICONIP 2002|
|Period||02/11/18 → 02/11/22|
Bibliographical noteFunding Information:
This paper was supported by Brain Science and Engineering Research program sponsored by Korean Ministry of Science and Technology.
© 2002 Nanyang Technological University.
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Information Systems
- Signal Processing