This study investigates an approach of knowledge discovery and data mining in insufficient databases. An application of Computational Taxonomy analysis demonstrates that the approach is effective in such a data mining process. The approach is characterized by the use ot…

Knowledge-intensive processes are widely used to recover from errors, handle exceptional cases and complaints, and to improve or adapt a process itself. In this context, evolved Business-Process Reengineering (BPR) techniques are changing to give some answers to this reality. In…

In omplete information is a problem in many aspe ts of a tual environments. Further- more, in many s enarios the knowledge is not represented in a risp way. It is ommon to nd fuzzy on epts or problems with…

The genetic algorithms have seen applied in knowledge discovery and specially for discovering association rules. In this paper, we explore the use of di erent rule quality measures in the tness function in a genetic algorithm for discovering association rules.…

The Semantic Web attempts to reach a state in the future where everything on the Web will no longer be only machine-readable, but also machine-understandable. An ontology is an explicit specification of a conceptualization. A conceptualization is an abstract, simplified…

When there is a need to understand the data stored in a database, one of the main requirements is being able to extract knowledge in the form of rules. Classification strategies allow extracting rules almost naturally. In this paper, the…

Software tools processing partially common set of data should share an understanding of what these data mean. Since ontologies have been used to express formally a shared understanding of information, we argue that they can be used to improve integration…

In today’s world, in both the public or private organizations, there exists the problem that the organizations have to create value, are changing, but the tools to measure them are not. On the other hand, in the current economy, the…