There exists a large amount of knowledge representation models. But most of them have significant limitations at the epistemic level. They do not have explanatory power. Most of them do not have means to represent some functional needs to work…

Fish disease diagnosis is a complicated process and requires high level of expertise, an expert system for fish disease diagnosis is considered as an effective tool to help fish farmers. However, many farmers have no computers and are not able…

The development of systems with the ability to reason about change notion and actions has been of great importance for the artificial intelligence community. The definition and implementation of systems capable of managing defeasible, incomplete, unreliable, or uncertain information has…

Classical methods for representing and reasoning with knowledge rely on the assumption that the available information is complete, certain and consistent. In real-world problems this is usually not the case, and Al has long dealt with the issue of finding…

In an m-machines n-jobs flow-shop sequencing problem each job consists of m operations and each operation requires a different machine, so n jobs have to be processed in the same sequence on m machines. The processing time of each job…

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…

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…

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…