DocumentCode
2467456
Title
Study and Comparison of Different Vocabulary Selection Methods: Application to Topic Detection of Arabic Documents
Author
Mellouli, Amal ; Jamoussi, Salma
Author_Institution
Miracle Lab., Inst. of Comput. Sci. & Multimedia, Sfax, Tunisia
fYear
2010
fDate
17-19 Dec. 2010
Firstpage
1273
Lastpage
1276
Abstract
In this paper we present many studies and comparisons of different methods of vocabulary selection applied to Topic Detection of some Arabic documents. The topic detection is realized by two methods: neuronal network and support vector machines (SVM). We tested and compared different vocabulary selection methods: word frequency per topic, entropy, Gini and “fselect” based on SVM.
Keywords
document handling; natural language processing; neural nets; support vector machines; Arabic documents; neuronal network; support vector machines; topic detection; vocabulary selection methods; Artificial neural networks; Frequency measurement; Indexes; Mutual information; Support vector machines; Training; Vocabulary; Arabic language; Multi layer Perceptron; SVM; Topic detection; neuronal network; vocabulary selection methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational and Information Sciences (ICCIS), 2010 International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-8814-8
Electronic_ISBN
978-0-7695-4270-6
Type
conf
DOI
10.1109/ICCIS.2010.314
Filename
5709514
Link To Document