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International Conference on Database and Expert Systems Applications

DEXA 2017: Database and Expert Systems Applications pp 67–79Cite as

On Computing Temporal Aggregates over Null Time Intervals

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10439))

Abstract

In a temporal database, each data tuple is accompanied by a time interval during which its attribute values are valid. In this paper, we consider the null time intervals, that is, time intervals not intersected by any time intervals in the temporal database. We deal with the problem of computing temporal aggregates over null time intervals with length constraints. By interval folding, we transform the problem into aggregates over stabbing groups, maximal stabbing interval sets. We describe the detailed algorithms and report the experimental results.

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References

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Acknowledgments

We would like to thank Prof. Yuichi Asahiro for the valuable advices that led to this paper. We also thank the anonymous reviewers for their valuable comments.

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Authors and Affiliations

  1. Graduate School of Information Science, Kyushu Sangyo University, 2-3-1, Mtsukadai, Higashi-ku, Fukuoka, 813-8503, Japan

    Kai Cheng

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  1. Kai Cheng
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Corresponding author

Correspondence to Kai Cheng .

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Editors and Affiliations

  1. University of Lyon, Villeurbanne, France

    Djamal Benslimane

  2. University of Milan, Milan, Italy

    Ernesto Damiani

  3. University of Michigan, Dearborn, Michigan, USA

    William I. Grosky

  4. Paul Sabatier University, Toulouse, France

    Abdelkader Hameurlain

  5. Wright State University, Dayton, Ohio, USA

    Amit Sheth

  6. Johannes Kepler University, Linz, Austria

    Roland R. Wagner

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Cheng, K. (2017). On Computing Temporal Aggregates over Null Time Intervals. In: Benslimane, D., Damiani, E., Grosky, W., Hameurlain, A., Sheth, A., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2017. Lecture Notes in Computer Science(), vol 10439. Springer, Cham. https://doi.org/10.1007/978-3-319-64471-4_7

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  • DOI: https://doi.org/10.1007/978-3-319-64471-4_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64470-7

  • Online ISBN: 978-3-319-64471-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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