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 cognitive diagnosis is defined as the abstract process of gathering information about the student's learning and transforming that information based on instructional decisions. A model that captures the expert knowledge of experienced professors and is used to design a…

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…

In the last decade, several argument-based formalisms have emerged, with application in many areas, such as legal reasoning, autonomous agents and multi-agent systems; many are based on Dung’s seminal work characterizing Abstract Argumentation Frameworks (AF).
Recent research in the area…

The appearance and continuous growth of virtual communities on the web imposes the challenge of coping with the large amount of information and knowledge these communities produce. The Semantic Web with its set of standards and technologies provides the basic…

Knowledge acquisition for systems based on knowledge can be called knowledge engineering, according to Feigenbaum (1980) who used the term to describe the reduction of a wide context of knowledge for a set of facts and rules. The term Knowledge…

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…

Effective document retrieval using domain knowledge and semantics is one of the major challenges in Information Retrieval. Over the last years, there has been a growing interest in ontologies as an artifact for human knowledge representation and a critical component…

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 of…