• DocumentCode
    442053
  • Title

    Automatic keyphrases extraction from document using backpropagation

  • Author

    Wang, Jia-bing ; Peng, Hong ; Hu, Jing-song

  • Author_Institution
    Sch. of Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
  • Volume
    6
  • fYear
    2005
  • fDate
    18-21 Aug. 2005
  • Firstpage
    3770
  • Abstract
    Automatic keyphrase extraction from documents is a task with many applications in information retrieval and natural language processing. Previously, Several keyphrase extraction methods have been proposed based on different techniques. In this paper a keyphrase extraction approach based on backpropagation is proposed. In order to determine whether a phrase is a keyphrase or not, the following features of a phrase in a given document are adopted: its term frequency TF and inverted document frequency IDF, whether or not it appears in the title or headings (subheadings) of the given document, and its distribution in the paragraphs of the given document. The algorithm is evaluated by the standard information retrieval metrics of precision and recall and human assessment. Experiment results show that this approach is competitive with other known methods.
  • Keywords
    backpropagation; feedforward neural nets; indexing; information retrieval; multilayer perceptrons; automatic document keyphrase extraction; backpropagation; information retrieval; multilayer feed-forward neural network; natural language processing; Application software; Backpropagation algorithms; Computer science; Data mining; Databases; Frequency measurement; Humans; Information retrieval; Natural language processing; Particle measurements; Keyphrase extraction; backpropagation; information retrieval; natural language processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
  • Conference_Location
    Guangzhou, China
  • Print_ISBN
    0-7803-9091-1
  • Type

    conf

  • DOI
    10.1109/ICMLC.2005.1527596
  • Filename
    1527596