The blind men and the elephant: on meeting the problem of multiple truths in data from clustering and pattern mining perspectives

摘要

In this position paper, we discuss how different branches of research on clustering and pattern mining, while rather different at first glance, in fact have a lot in common and can learn a lot from each other’s solutions and approaches. We give brief introductions to the fundamental problems of different sub-fields of clustering, especially focusing on subspace clustering, ensemble clustering, alternative (as a variant of constraint) clustering, and multiview clustering (as a variant of alternative clustering). Second, we relate a representative of these areas, subspace clustering, to pattern mining. We show that, while these areas use different vocabularies and intuitions, they share common roots and they are exposed to essentially the same fundamental problems; in particular, we detail how certain problems currently faced by the one field, have been solved by the other field, and vice versa.