The rapid growing of information technology (IT) motivates and makes competitive advantages in health care industry. Nowadays, many hospitals try to build a successful customer relationship management (CRM) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. Many hospitals have large data warehouses containing customer ...

Interval type-2 fuzzy sets, each of which is characterized by the footprint of uncertainty, are a very useful means to depict the linguistic information in the process of decision making. In this article, we investigate the group decision making problems in which all the linguistic information provided by the decision makers is expressed as interval type-2 fuzzy decision matrices where each of ...

The goal of attribute reduction is to find a minimal subset (MS) R of the condition attribute set C of a dataset such that R has the same classification power as C. It was proved that the number of MSs for a dataset with n attributes may be as large as (nn/2) and the generation of all of them is an NP-hard problem. The main reason for this is the intractable space complexity of the conversion o...

Extensible programming languages and their compilers are experimental systems that use highly modular specifications of languages and language extensions in order to allow a variety of language features to be easily imported, by the programmer, into his or her programming environment. Our framework for extensible languages is based on higher-order attribute grammars extended with a mechanism ca...

Quality attribute workshops (QAW) provide a method for evaluating the architecture of a software-intensive system during the acquisition phase of major programs. The architecture is evaluated against a number of critical quality attributes, such as availability, performance, security, interoperability, and modifiability. The evaluation is based on test cases that capture questions and concerns ...

Discretization is a process of converting a continuous attribute into an attribute that contains small number of distinct values. One of the major reasons for discretizing an attribute is that some of the machine learning algorithms perform poorly with continuous attribute and thus require front-end discretization of the input data. The paper describes a Fast Class-Attribute Interdependence Max...

The effectiveness of using the semantic attributes of verbs has been shown in various kinds of natural processing systems, such as machine translation systems. The addition of an attribute value is, however, time-consuming and must be performed by hand by an expert on the attribute value. In this paper, two methods for efficiently adding verbal semantic attributes to a Japanese-to-English valen...

Rough sets theory is an effective mathematical tool dealing with vagueness and uncertainty. It has been applied in a variety of fields such as data mining, pattern recognition or process control. It is very important to compute the attribute reduction in real applications of rough set theory. To compute the optimal attribute reduction is NP-hard. Many heuristic attribute reduction algorithms wi...

Because of the complexity of decision-making environment, the uncertainty of fuzziness and the uncertainty of grey maybe coexist in the problems of multi-attribute group decision making. In this paper, we study the problems of multi-attribute group decision making with hybrid grey attribute data (the precise values, interval numbers and linguistic fuzzy variables coexist, and each attribute val...