• 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