Abstract
In various approaches, data cubes are pre-computed in order to efficiently answer Olap queries. Such cubes are also successfully used for multidimensional analysis of data streams. In this paper, we address the issue of performing cube comparisons in order to exhibit trend reversals between two cubes. Mining such trend changes provides users with a novel and specially interesting knowledge. For capturing the latter, we introduce the concept of emerging cube. Moreover, we provide a condensed representation of emerging cubes which avoids to compute two underlying cubes. Finally, we study an algorithmic way to achieve our representation using cube maximals and cube transversals.
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Nedjar, S., Casali, A., Cicchetti, R., Lakhal, L. (2007). Emerging Cubes for Trends Analysis in Olap Databases. In: Song, I.Y., Eder, J., Nguyen, T.M. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2007. Lecture Notes in Computer Science, vol 4654. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74553-2_13
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DOI: https://doi.org/10.1007/978-3-540-74553-2_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74552-5
Online ISBN: 978-3-540-74553-2
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