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Mining Interesting Aggregate Tuples

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Intelligent Systems and Applications (IntelliSys 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 824))

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Abstract

In business intelligence, the concept of data cube offers aggregate views over multiple dimensions of business. Computing the data cube is a challenge because of the exponential number of cuboids. This number is not only an important problem of computing, but also of searching for what is interesting or useful in the data cube. This paper presents the concept of interesting aggregate tuple that can be useful for managers to decide on their business. This concept is useful because (i) interesting aggregate tuples are those with important and credible aggregate values, and (ii) the number of interesting aggregate tuples is very small that can be considered by humans. The algorithm for searching for interesting aggregate tuples is implemented and experienced on the real datasets.

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Authors and Affiliations

  1. Aix-Marseille Univ, Université de Toulon, CNRS, LIS, DANA, Marseille, France

    Viet Phan-Luong

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  1. Viet Phan-Luong
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Correspondence to Viet Phan-Luong .

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Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

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Phan-Luong, V. (2024). Mining Interesting Aggregate Tuples. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2023. Lecture Notes in Networks and Systems, vol 824. Springer, Cham. https://doi.org/10.1007/978-3-031-47715-7_16

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