Abstract
Many organizations possess large databases collected over a long period of time. Analysis of such databases might be strategically important for further growth of the organizations. For instance, it might be of interest to learn about interesting changes in sales over time. In this chapter, we introduce a new pattern, called notch, of an item in time-stamped databases. Based on this notion, we propose a special kind of notch, called a generalized notch and subsequently, a specific type of generalized notch, called an iceberg, in time-stamped databases. We design an algorithm for mining interesting icebergs in time-stamped databases. We also present experimental results obtained for both synthetic and real-world databases.
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Adhikari, A., Adhikari, J. (2015). Mining Icebergs in Different Time-Stamped Data Sources. In: Advances in Knowledge Discovery in Databases. Intelligent Systems Reference Library, vol 79. Springer, Cham. https://doi.org/10.1007/978-3-319-13212-9_7
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DOI: https://doi.org/10.1007/978-3-319-13212-9_7
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