Cube Interestingness: Novelty, Relevance, Peculiarity and Surprise
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In this paper, we discuss methods to assess the interestingness of a query in an environment of data cubes. We assume a hierarchical multidimensional database, storing data cubes and level hierarchies. We provide a systematic taxonomy of the dimensions of interestingness, and specifically, relevance, surprise, novelty, and peculiarity. We propose specific measures and algorithms for assessing the different dimensions of cube query interestingness in a quantitative fashion.
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