The use of end-to-end data mining methodologies such as CRISP-DM, KDD process, and
SEMMA has grown substantially over the past decade. However, little is known as to how …

Despite the hype around data analytics, the success rate of analytics initiatives remains very
low and the value of data in organisations is left hidden. Various research studies show that …

With the ever-increasing diffusion of smart devices and Internet of Things (IoT) applications,
a completely new set of challenges have been added to the Data Mining domain. Edge …

Purpose The purpose of this paper is to depict how Kaizen and continuous improvement (CI)
are represented in scientific journals focusing on quality management (QM) from the 1980s …

Data mining approach has been successfully implemented in higher education and emerge
as an interesting area in educational data mining research. The approach is intended for …

Abstract Virtual Learning Environments (VLE), such as Moodle and Blackboard, store vast
data to help identify students' performance and engagement. As a result, researchers have …

In this work, an innovative approach of multi-criteria decision-making method guided by
rough set theory is researched to predict diabetes. Diabetes is the root cause of various …

El avance tecnológico ha permitido a las organizaciones en todos los niveles almacenar
grandes volúmenes de datos. Sin embargo, un problema al cual se están enfrentando …

Comprehensibility in modeling is the ability of stakeholders to understand relevant aspects
of the modeling process. In this article, we provide a framework to help guide exploration of …

The recent emergence of clouds with large, virtualized pools of compute and storage
resources raises the possibility of a new compute paradigm for scientific research. With …