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Is Comprehension Useful for Mobile Semantic Search Engines?

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Neural Information Processing. Theory and Algorithms (ICONIP 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6443))

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Abstract

Semantic web is gaining popularity as a candidate for next generation World Wide Web. In recent years, there has been a tremendous increase of using Internet on mobile devices and search engines are considered essential for Internet users. The existing search engines have been designed for powerful computers and are highly resource hungry, while mobiles have limited computational resources. In this paper, we study the use of comprehension for aiding the search engine results for mobile users. Our preliminary evaluation shows the promising results for comprehension generation.

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Author information

Authors and Affiliations

  1. School of EE&T, University of New South Wales (UNSW), Australia

    Ahmad Ali Iqbal

  2. National Information and Communication Technology Australia (NICTA), Australia

    Aruna Seneviratne

Authors
  1. Ahmad Ali Iqbal
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  2. Aruna Seneviratne
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Editor information

Editors and Affiliations

  1. School of Information Technology, Murdoch University, 6150, Murdoch, WA, Australia

    Kok Wai Wong

  2. The Australian National University, 0200, Canberra, ACT, Australia

    B. Sumudu U. Mendis

  3. School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Northfields Avenue, 2522, P.O. Box, Wollongong, NSW, Australia

    Abdesselam Bouzerdoum

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© 2010 Springer-Verlag Berlin Heidelberg

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Iqbal, A.A., Seneviratne, A. (2010). Is Comprehension Useful for Mobile Semantic Search Engines?. In: Wong, K.W., Mendis, B.S.U., Bouzerdoum, A. (eds) Neural Information Processing. Theory and Algorithms. ICONIP 2010. Lecture Notes in Computer Science, vol 6443. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17537-4_38

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  • DOI: https://doi.org/10.1007/978-3-642-17537-4_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17536-7

  • Online ISBN: 978-3-642-17537-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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