Document summarisation on mobile devices using non-negative matrix factorisation

  • Authors:

  • Hiroya Kitagawa;El-Sayed Atlam;Masao Fuketa;Kazuhiro Morita;Jun-ichi Aoe

  • Affiliations:

  • Department of Information Science and Intelligent Systems, Faculty Engineering, University of Tokushima, 2-1 Minami Josanjima, Tokushima, 770-8506, Japan;Department of Information Science and Intelligent Systems, Faculty Engineering, University of Tokushima, 2-1 Minami Josanjima, Tokushima, 770-8506, Japan;Department of Information Science and Intelligent Systems, Faculty Engineering, University of Tokushima, 2-1 Minami Josanjima, Tokushima, 770-8506, Japan;Department of Information Science and Intelligent Systems, Faculty Engineering, University of Tokushima, 2-1 Minami Josanjima, Tokushima, 770-8506, Japan;Department of Information Science and Intelligent Systems, Faculty Engineering, University of Tokushima, 2-1 Minami Josanjima, Tokushima, 770-8506, Japan

  • Venue:
  • International Journal of Computer Applications in Technology
  • Year:
  • 2013

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Abstract

With the rapid advancement of wireless communication technologies, mobile devices become very useful ubiquitous terminals. Typical devices are mobile phones with web browsing facilities, but there are many types of computing abilities. A low-end mobile phone has less ability than a smart phone with a complete operating system providing a platform for application developers. In general, there are typical shortcomings for mobile phone devices such as narrow bandwidth and the small-sized display. Therefore, document summarisation on mobile phones is one of the most convenient applications. This paper proposes compact and fast approaches that can summarise documents on mobile devices efficiently. The proposed method improves unsupervised schemes using the original non-negative matrix factorisation (NMF) that can determine the paragraph precedence without morphological and syntax analyses. In order to speed up the summarisation, the proposed technique is applied to the NMF method. From simulation results for test data of DUC2006, it turns out that the matrix size could be reduced by about 95% and the precision of summarisation speeding becomes 8.5 times faster than the original method without degrading the precision of extracted paragraphs.