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iExplore: Accelerating Exploratory Data Analysis by Predicting User Intention

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Database Systems for Advanced Applications (DASFAA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10828))

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Abstract

Exploratory data analysis over large datasets has become an increasingly prevalent use case. However, users are easily overwhelmed by the data and might take a long time to find interesting facts. In this paper, we design a system called iExplore to assist users in doing this time-consuming data exploration task through predicting user intention. Moreover, we propose an intention model to help the iExplore system have a comprehensive understanding of user’s intention. Thus, the exploratory process can be accelerated by the intention-driven recommendation and prefetching mechanisms. Extensive experiments demonstrate that the intention-driven iExplore system can significantly lighten the burden of users and facilitate the exploratory process.

The work is supported by the NSFC (No. 61732004) and the Shanghai Innovation Action Project (Grant No. 16DZ1100200).

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Notes

  1. 1.

    http://cas.sdss.org/dr7/en.

  2. 2.

    http://skyserver.sdss.org/log/en/traffic/sql.asp.

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Author information

Authors and Affiliations

  1. School of Computer Science, Fudan University, Shanghai, China

    Zhihui Yang, Jiyang Gong, Chaoying Liu, Yinan Jing, Zhenying He, Kai Zhang & X. Sean Wang

  2. Shanghai Key Laboratory of Data Science, Shanghai, China

    Zhihui Yang, Jiyang Gong, Chaoying Liu, Yinan Jing, Zhenying He, Kai Zhang & X. Sean Wang

  3. Shanghai Institute of Intelligent Electronics & Systems, Shanghai, China

    X. Sean Wang

Authors
  1. Zhihui Yang
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  2. Jiyang Gong
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  3. Chaoying Liu
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  4. Yinan Jing
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  5. Zhenying He
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  6. Kai Zhang
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  7. X. Sean Wang
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Corresponding authors

Correspondence to Yinan Jing , Zhenying He or X. Sean Wang .

Editor information

Editors and Affiliations

  1. Simon Fraser University, Burnaby, BC, Canada

    Jian Pei

  2. Aristotle University of Thessaloniki, Thessaloniki, Greece

    Yannis Manolopoulos

  3. University of Queensland, Brisbane, QLD, Australia

    Shazia Sadiq

  4. University of Western Australia, Crawley, WA, Australia

    Jianxin Li

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Yang, Z. et al. (2018). iExplore: Accelerating Exploratory Data Analysis by Predicting User Intention. In: Pei, J., Manolopoulos, Y., Sadiq, S., Li, J. (eds) Database Systems for Advanced Applications. DASFAA 2018. Lecture Notes in Computer Science(), vol 10828. Springer, Cham. https://doi.org/10.1007/978-3-319-91458-9_9

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  • DOI: https://doi.org/10.1007/978-3-319-91458-9_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91457-2

  • Online ISBN: 978-3-319-91458-9

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