A Conceptual Framework of Data Mining - Data Mining: Foundations and Practice - page 487

A Conceptual Framework of Data Mining

Yiyu Yao 1 , Ning Zhong 2 , and Yan Zhao 1

1

Department of Computer Science, University of Regina
Regina, Saskatchewan, Canada S4S 0A2
[e-mail], [e-mail]

2

Department of Information Engineering, Maebashi Institute of Technology
460-1, Kamisadori-Cho, Maebashi 371, Japan
[e-mail]

Summary. The study of foundations of data mining may be viewed as a scientific
inquiry into the nature of data mining and the scope of data mining methods.
There is not enough attention paid to the study of the nature of data mining,
or its philosophical foundations. It is evident that the conceptual studies of data
mining as a scientific research field, instead of a collection of isolated algorithms, are
needed for a further development of the field. A three-layered conceptual framework
is thus proposed, consisting of the philosophy layer, the technique layer and the
application layer. Each layer focuses on different types of fundamental questions
regarding data mining, and they jointly form a complete characterization of the
field. The layered framework is demonstrated by applying it to three sub-fields of
data mining, classification, measurements, and explanation-oriented data mining.

1 Introduction

With the development and success of data mining, many researchers became
interested in the fundamental issues, namely, the foundations of data min-
ing [2, 7, 8, 22]. The study of foundations of data mining should be viewed as
a scientific inquiry into the nature of data mining and the scope of data min-
ing methods . This simple view separates two important issues. The study of
the nature of data mining concerns the philosophical, theoretical and mathe-
matical foundations of data mining; while the study of data mining methods
concerns its technological foundations by focusing on the algorithms and tools.
A review of the existing studies show that not enough attention has been
paid to the study of the nature of data mining, more specifically, to the philo-
sophical foundations of data mining [22]. Although three dedicated interna-
tional workshops have been held [6-8], there still do not exist well-accepted
and non-controversial answers to many basic questions, such as, what is data
mining? what makes data mining a distinctive study? what are the founda-
tions of data mining? What is the scope of the foundations of data mining?