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International Conference on Knowledge-Based and Intelligent Information and Engineering Systems

KES 2005: Knowledge-Based Intelligent Information and Engineering Systems pp 540–546Cite as

Supporting Exploratory Data Analysis by Preserving Contexts

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3681))

Abstract

The goal of the research presented in this paper is to support users in exploring a huge amount of data for the purpose of decision-making and problem-solving. Our approach is to design human-computer interaction as a natural discourse between the user who explores the data and the system that supports the user’s exploration process. For that purpose, we developed a prototype system named InTREND that interprets the user’s natural language query and presents statistical charts as a result of the query. InTREND encourages iterative exploration by maintaining the context of past interactions and uses this context to improve discourse with the user. This paper explains our research motivation and presents a framework for supporting exploratory data analysis. Our user studies evaluate the context preservation mechanisms of InTREND.

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Author information

Authors and Affiliations

  1. NTT Communication Science Labs., NTT Corp., 2-4 Hikaridai, Seikacho, Sorakugun, Kyoto, 619-0237, Japan

    Mitsunori Matsushita

Authors
  1. Mitsunori Matsushita
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Editor information

Editors and Affiliations

  1. School of Business, La Trobe University, 3086, Melbourne, Victoria, Australia

    Rajiv Khosla

  2. Centre for SMART systems Engineering Research Centre, University of Brighton, Moulsecoomb, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2005 Springer-Verlag Berlin Heidelberg

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Matsushita, M. (2005). Supporting Exploratory Data Analysis by Preserving Contexts. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552413_78

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  • DOI: https://doi.org/10.1007/11552413_78

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28894-7

  • Online ISBN: 978-3-540-31983-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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