This paper proposes a method for ranking decision making units (DMUs) using some of the multiple criteria decision making / multiple attribute decision making          (MCDM /MADM) techniques, namely, interval analytic hierarchy process (IAHP)          and the technique for order preference by similarity to an ideal solution (TOPSIS).          Since the efficiency score of unity is assigned to ...

Consumer choice in surveys and in the marketplace reflects a complex process of screening and evaluating choice alternatives. Behavioral and economic models of choice processes are difficult to estimate when using stated and revealed preferences because the underlying process is latent. This paper introduces Bayesian methods for estimating two behavioral models that eliminate alternatives using...

The discovery of knowledge in databases is currently a very active research area. Many discovery systems adapt traditional attribute{based learners for the extraction of patterns. They have been, however, restricted by their inability to incorporate background knowledge into the learning process. In this paper an attribute{based learning algorithm, called SIDEC, which can incorporate a restrict...

Rule learning systems use features as the main building blocks for rules. A feature can be a simple attribute-value test or a test of the validity of a complex domain knowledge relationship. Most existing concept learning systems generate features in the rule construction process. However, the separation of feature generation and rule construction processes has several theoretical and practical...

Both the instance level knowledge and the attribute level knowledge can improve clustering quality, but how to effectively utilize both of them is an essential problem to solve. This paper proposes a wrapper framework for semi-supervised clustering, which aims to gracely integrate both kinds of priori knowledge in the 598 J. L. Wang, S.Y. Wu, C. Wen, G. Li clustering process, the instance level...

There are many problems in construction process, such as fragmentation, budget overrun, time overrun and high waste, most of which are supply chain problems and often caused by the lack of coordination and information sharing across organizations in the supply chains. Supply chain coordination (SCC) is a critical success factor for the application of supply chain management to effectively impro...

-In order to solve the problem of the redundant information to distinguish in the risk decision-making, in this paper, the data mining algorithms based on Rough Sets is studied. And we know the risk decision-making is an important aspect in the management practice. In the risk decision process of a project decision-making, it is necessary to use the algorithm to discover valuable knowledge and ...