Information Retrieval Systems normally deal with keywordbased technologies. Although those systems reach satisfactory results, they aren’t able to answer more complex queries done by users, especially those directly in natural language. To do that, there are the KnowledgeBased Systems, which…

We propose a framework for studying the effect of KDD on CRM in the Egyptian banking sector. We believe that the KDD process and applications may perform a significant role in Egyptian banks to improve CRM, in particular for customer…

We discuss how data mining, patternbases and databases can be integrated into inductive databases, which make data mining an inductive query process. We propose a software architecture for such inductive databases, and extend this architecture to support the clustering of…

The knowledge imperfections should be considered when modeling complex problems. A solution is to develop a model that reduces the complexity and another option is to represent the imperfections: uncertainty, vagueness and incompleteness in the knowledge base. This paper proposes…

In the information age, knowledge leads to profits, power and success. As an ancestor of data mining, machine learning has concerned itself with discovery of new knowledge on its own. This paper presents experiment results produced by genetic algorithms in…

In a defeasible argumentation formalism, an argument is used as a defeasible reason for supporting conclusions. A conclusion q will be considered valid only when the argument that supports it become a justification. Building a justification involves the construction of…

The general objective of this thesis is the development of an adaptive technique for extracting knowledge in large databases. Nowadays, technology allows storing huge volumes of information. For this reason, the availability of techniques that allow, as a first stage,…

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…

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…