Recently, there has been enormous growth in the amount of commercial and scientific data, such as protein sequences, retail transactions, and web-logs. Such datasets consist of sequence data that have an inherent sequential nature. However, few existing clustering algorithms consider...

Knowledge management is a newly emerging, interdisciplinary business model dealing with all aspects of knowledge within the context of the firm, including knowledge creation, codification, sharing, and how these activities promote learning and innovation. In practice, knowledge management...

We discuss our reasons for bringing out this special issue and, after a review of the pertinent literature, propose a conceptual framework for the subject under examination. Using this framework, we offer an overview of the articles by segmenting them into categories and discussing their...

We study the applicability of the pattern recognition methodology "rough set data analysis" (RSDA) in the field of meta analysis. We give a summary of the mathematical and statistical background and then proceed to an application of the theory to a meta analysis of empirical studies dealing with...

We introduce methods from statistical learning theory to the field of conjoint analysis for preference modeling. We present a method for estimating preference models that can be highly nonlinear and robust to noise. Like recently developed polyhedral methods for conjoint analysis, our method is...

The research on financial engineering by means of genetic programming is gradually popular and appealing. For example, Kaboudan (1999, 2001) and Iba and Sasaki (1999), Iba and Sasaki (1999), used standard GP to evolve forecasting models. Neely, et al. (1997), Allen and Karjalainen (1999), Fyfe...