GDL

Two Text Classifiers in Online Discussion: Support Vector Machine vs Back-Propagation Neural Network

Journal from gdlhub / 2016-11-12 03:28:41
Oleh : E. Erlin, R. Rahmiati, Unang Rio, Telkomnika
Dibuat : 2014-03-01, dengan 1 file

Keyword : text categorization, support vector machine, back-propagation neural network
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/17

The purpose of this research is to compare the performance of two text classifiers; support vector machine (SVM) and back-propagation neural network (BPNN) within categorize messages from an online discussion. SVM has been recognized as one of the best algorithm for text categorization. BPNN is also a popular categorization method that can handle linear and non linear problems and can achieve good result. However, using SVM and BPNN in online discussion is rare. In this research, several SVM data are trained in multi-class categorization to classify the same set with BPNN. The effectiveness of these two text classifiers are measured and then statistically compared based on error rate, precision, recall and F-measure. The experimental result shows that for text message categorization in online discussion, the performances of SVM outperform BPNN in term of error rate and precision; and falls behind BPNN in term of recall and F-measure.

Deskripsi Alternatif :

The purpose of this research is to compare the performance of two text classifiers; support vector machine (SVM) and back-propagation neural network (BPNN) within categorize messages from an online discussion. SVM has been recognized as one of the best algorithm for text categorization. BPNN is also a popular categorization method that can handle linear and non linear problems and can achieve good result. However, using SVM and BPNN in online discussion is rare. In this research, several SVM data are trained in multi-class categorization to classify the same set with BPNN. The effectiveness of these two text classifiers are measured and then statistically compared based on error rate, precision, recall and F-measure. The experimental result shows that for text message categorization in online discussion, the performances of SVM outperform BPNN in term of error rate and precision; and falls behind BPNN in term of recall and F-measure.

Beri Komentar ?#(0) | Bookmark

Properti	Nilai Properti
ID Publisher	gdlhub
Organisasi	Telkomnika
Nama Kontak	Herti Yani, S.Kom
Alamat	Jln. Jenderal Sudirman
Kota	Jambi
Daerah	Jambi
Negara	Indonesia
Telepon	0741-35095
Fax	0741-35093
E-mail Administrator	elibrarystikom@gmail.com
E-mail CKO	elibrarystikom@gmail.com