Knowledge Management (KM) has become a key success factor in diverse fields, given the importance of knowledge as a significant organizational asset. In order to solve problems and support complex decision-making processes, knowledge and experience have to be transmitted across individuals, business units and organizations. Thus, Knowledge Sharing (KS) can be considered as the basic element of ...

1 Uncertain knowledge can be modeled by using graded probabilities rather than binary truth-values, but so far a completely satisfactory integration of logic and probability has been lacking. In particular the inability of confirming universal hypotheses has plagued most if not all systems so far. We address this problem head on. The main technical problem to be discussed is the following: Give...

Within large corpora of texts, Knowledge-Rich Contexts (KRCs) are a subset of sentences containing information that would be valuable to a human for the construction of a knowledge base. The entry point to the discovery of KRCs is the automatic identification of Knowledge Patterns (KPs) which are indicative of semantic relations. Machine readable dictionary serves as our starting point for inve...

The models of the evolution researchers are focused on the origin and the multiplication of organisms. This paper introduces a possible approach of the evolution of organisms being concerned in the appearance of the intelligence. This process is self developing and adaptive, producing the knowledge graph, which is the result of a lifelong data capturing and acquisition task of an artificial dig...

The ability of farmers to acquire knowledge to make decisions is limited by the information quality and applicability. Inconsistencies in information delivery and standards for the integration of information also limit decision making processes. This research uses a similar approach to the Knowledge Discovery in Databases (KDD) methodology to develop an ICT based framework which can be used to ...

We demonstrate the use of an unsupervised learning technique called genetic algorithms to discover the association between a concept and its key attributes in concept characterization. The resulting conceptattribute associations are important domain concepts for knowledge engineers to structure interviews with the experts or to prepare representative data for inductive inference. Examples based...

This paper reports on research conducted to explore the problems that organisations have with respect to a key first step in effective Knowledge Management: Knowledge Identification. The paper reports on the results from an exploratory, interpretive investigation on the problems organisations have with respect to identifying what knowledge exists within their boundaries. The research conducted ...