Abstract
“Black hole” are widely spread in the mobile communication data, which will highly downgrade the mobile service quality. OLAP tools are extensively used for the decision-support application in the multidimensional data model, which just like the mobile communication case. As different dimensions of the mobile data are incomparable and, thus, can hardly generate one unique final value that satisfies all dimensions. We exploit the skyline operator as the postoperation while building data cubes, named as data cube of skyline. As the skyline of a cuboid is not derivable from another cuboid and the skyline operation is holistic, which makes this problem even challeging. In this paper, we propose a method in materializing the cube of skyline in the big communication data and proof its effectiveness and efficiency by extensive experiments.
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Notes
- 1.
For example, it’s meaningless to compare “year” dimension to “region” dimension.
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This work was supported by Natural Science Foundation of China (No. 61170003).
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Zhang, J., Hong, S., Lin, Y., Mou, Y., Li, H. (2017). Finding the Typical Communication Black Hole in Big Data Environment. In: Tan, Y., Takagi, H., Shi, Y. (eds) Data Mining and Big Data. DMBD 2017. Lecture Notes in Computer Science(), vol 10387. Springer, Cham. https://doi.org/10.1007/978-3-319-61845-6_26
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DOI: https://doi.org/10.1007/978-3-319-61845-6_26
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