Cube Interestingness: Novelty, Relevance, Peculiarity and Surprise

12/06/2022

∙

by   Dimos Gkitsakis, et al.

∙

0

∙

share

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.