A Framework for Learning Cell Interestingness from Cube Explorations

Abstract

In this paper, we discuss the problem of organizing the different ways of computing the interestingness of a particular cell derived from a cube in the context of a hierarchical, multidimensional space. We start from an in-depth study of the interestingness aspects in the study of human behavior and include in our survey the approaches taken by computer-science efforts in the area of data mining and user recommendations. We move on to structure interestingness along different fundamental, high level aspects, and, due to their high-level nature, we also move towards much more concrete data-oriented definitions of intertestingness aspects.

Enhancing Cubes with Models to Describe Multidimensional Data

“…Specifically, we address challenge (ii) by experimenting two techniques to automatically set the number of model components, and challenge (iii) by proposing and validating a new interestingness measure for model components. Notably, this measure is consistent with the multi-facets interestingness scheme introduced by Marcel et al (2019). The present work gives a precise and motivated definition for both the facets used and the way they are aggregated to form a global score.…”

“…The measure proposed by Chédin et al (2020) to assess the interestingness of component c is based on the idea of prior belief (Bie 2013): specifically, it defines the interestingness of c as the difference of belief for corresponding cells in the cube before and after the application of the intention. In this work we develop a more sophisticated model, based on three facets of interestingness identified by Marcel et al (2019) Therefore, for each component, we give three scores, one for each interestingness facet. We then define the global interestingness as a linear combination of the three facets.…”

“…Note thatMarcel et al (2019) describe one more facet of interestingness, namely, relevance. Relevance is not considered in this work because it would largely overlap with peculiarity.…”