Data mining has become a well established discipline within the domain of Artificial Intelligence (AI) and Knowledge Engineering (KE). It has its roots in machine learning and st...
Knowledge engineering techniques are becoming useful and popular components of hybrid integrated systems used to solve complicated practical problems in different fields. Knowledge...
This paper gives an overview about the development of the field of Knowledge Engineering over the last 15 years. We discuss the paradigm shift from a transfer view to a modeling v...
In knowledge engineering, modelling knowledge is the process of structuring knowledge before implementation. A crucial part of system development depends on the acquiring and struc...
Thls paper proposes a new perceptual approach to noisy X-ray image segmentation. It consistsof the five major step :(1)Pre -segmentation, (2)Improved region growing, (3 ) Object de...
With the advent of the Web and the efforts towards a Semantic Web the nature of knowledge engineering has changed drastically. In this position paper we propose four principles fo...
Enabling a domain expert to maintain his own knowledge in a Knowledge Based System has long been an ideal for the Knowledge Engineering community. In this paper we report on our ex...
One problem faced in knowledge engineering for Bayesian networks is the exponential growth of the number of parameters in their conditional probability tables (CPTs). The most comm...
After the concept of industry cluster was tangibly applied in many countries, SMEs trended to link to each other to maintain their competitiveness in the market. The major key succ...
Abstract The paper analyzes UML, the well known software engineering tool, from the knowledge engineering perspective. The goal of the paper is to evaluate UML as the possible desi...