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Data mining has been defined as "The nontrivial extraction of implicit, previously unknown, and potentially useful information from data". Clustering is the automated search for group of related observations in a data set. The K-Means method is one of the most commonly used clustering techniques for a variety of applications. This paper proposes a method for making the K-Means algorithm...
Top-k processing in Uncertain Databases is semantically and computationally different from traditional top-k processing. The interplay between score and uncertainty information makes traditional top-k processing techniques inapplicable to uncertain databases. The existing approaches are all based on the assumption that the underlying data are exact (or certain). We construct a framework that encapsulates...
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