A theoretical framework for exploratory data mining: Recent insights and challenges ahead

Abstract

Exploratory Data Mining (EDM), the contemporary heir of Exploratory Data Analysis (EDA) pioneered by Tukey in the seventies, is the task of facilitating the extraction of interesting nuggets of information from possibly large and complexly structured data. Major conceptual challenges in EDM research are the understanding of how one can formalise a nugget of information (given the diversity of types of data of interest), and how one can formalise how interesting such a nugget of information is to a particular user (given the diversity of types of users and intended purposes). In this Nectar paper we briefly survey a number of recent contributions made by us and collaborators towards a theoretically motivated and practically usable resolution of these challenges. © 2013 Springer-Verlag.