DocumentCode
245656
Title
Web Classification Using Deep Belief Networks
Author
Shu Sun ; Fang Liu ; Jun Liu ; Yinan Dou ; Hua Yu
Author_Institution
Beijing Key Lab. of Network, Beijing Univ. of Posts & Telecommun., Beijing, China
fYear
2014
fDate
19-21 Dec. 2014
Firstpage
768
Lastpage
773
Abstract
In recent years, deep learning approaches have gained significant interest as a way of building hierarchical representations from unlabeled data. These deep learning approaches have been applied to image recognition, voice recognition and text processing. However, to our knowledge, the deep learning approaches have not been extensively studied for web data. In this paper, we apply deep belief networks to web data and evaluate the algorithm on various classification experiments by comparing its performance with that of the SVM classification algorithm. In addition, the experiments show good performance of the deep belief networks for various classification tasks.
Keywords
Internet; belief networks; learning (artificial intelligence); pattern classification; support vector machines; SVM classification algorithm; Web classification; Web data; deep belief networks; deep learning approach; hierarchical representations; unlabeled data; Accuracy; Algorithm design and analysis; Electronic commerce; Support vector machines; Training; Training data; Vectors; DBN; Deep Learning; SVM; Web Classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4799-7980-6
Type
conf
DOI
10.1109/CSE.2014.158
Filename
7023668
Link To Document