A major challenge in credit card portfolio management is to classify and predict credit cardholders' behaviors in a reliable precision because cardholders' behaviors are rather dynamic in nature. This is crucial for creditors because it allows them to take proactive actions and minimize...

Despite the rapid development, the field of data mining and knowledge discovery (DMKD) is still vaguely defined and lack of integrated descriptions. This situation causes difficulties in teaching, learning, research, and application. This paper surveys a large collection of DMKD literature to...

The analytical network process (ANP) has been widely used to evaluate the suppliers, an important subject in supply chain management. We propose an integrated ANP-based evaluation model, which systematically examines six key decision-making modules. They are: questionnaire design, matrix...

Cardinal and ordinal inconsistencies are important and popular research topics in the study of decision making with pair-wise comparison matrices (PCMs). Few of the currently-employed tactics are capable of simultaneously dealing with both cardinal and ordinal inconsistency issues in one model,...

The consistency of the pairwise comparison matrix (PCM) has been extensively studied in the Analytic Hierarchy Process. Most of the existing approaches for the consistency test of the PCM are based on the consistency ratio threshold (0.1) introduced by Saaty (1977). To accurately measure the...

In this paper, we carry out a study about the main themes treated by the International Journal of Information Technology & Decision Making during its first 10 years (2002–2011). The themes are detected, quantified and visualized using an approach that combines performance analysis and science...

The derivation of a priority vector from a pair-wise comparison matrix (PCM) is an important issue in the Analytic Hierarchy Process (AHP). The existing methods for the priority vector derivation from PCM include eigenvector method (EV), weighted least squares method (WLS), additive...

In many applications such as credit risk management, data are represented as high-dimensional feature vectors. It makes the feature selection necessary to reduce the computational complexity, improve the generalization ability and the interpretability. In this paper, we present a novel feature...

Software development involves plenty of risks, and errors exist in software modules represent a major kind of risk. Software defect prediction techniques and tools that identify software errors play a crucial role in software risk management. Among software defect prediction techniques,...