An overview of emerging pattern mining in supervised descriptive rule discovery: taxonomy, empirical study, trends, and prospects. (18th October 2017)

• Record Type: Journal Article
• Authors: García‐Vico, A.M.; Carmona, C.J.; Martín, D.; García‐Borroto, M.; del Jesus, M.J.
• Is Part Of: Wiley interdisciplinary reviews. Volume 8:Number 1(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-10-18
• Subjects: Data mining -- Periodicals; 006.31205
• DOI: 10.1002/widm.1231
• Languages: English
• ISSNs: 1942-4787

Abstract

Abstract : Emerging pattern mining is a data mining task that aims to discover discriminative patterns, which can describe emerging behavior with respect to a property of interest. In recent years, the description of datasets has become an interesting field due to the easy acquisition of knowledge by the experts. In this review, we will focus on the descriptive point of view of the task. We collect the existing approaches that have been proposed in the literature and group them together in a taxonomy in order to obtain a general vision of the task. A complete empirical study demonstrates the suitability of the approaches presented. This review also presents future trends and emerging prospects within pattern mining and the benefits of knowledge extracted from emerging patterns. WIREs Data Mining Knowl Discov 2018, 8:e1231. doi: 10.1002/widm.1231 This article is categorized under: Fundamental Concepts of Data and Knowledge > Knowledge Representation Fundamental Concepts of Data and Knowledge > Motivation and Emergence of Data Mining Abstract : The main objective of this paper is to review the emerging pattern mining from descriptive induction. It provides a taxonomy of the differentes approaches proposed and they are categorised according to the objectives of descriptive knowledge.