Knowledge discovery by accuracy maximization

Knowledge discovery by accuracy maximization.

Here we describe KODAMA (knowledge discovery by accuracy maximization), an unsupervised and semisupervised learning algorithm that performs feature extraction from noisy and high-dimensional data. Unlike other data mining methods, the peculiarity of KODAMA is that it is driven by an integrated procedure of cross-validation of the results. The discovery of a local manifold's topology is led by a...

Knowledge Discovery by Design

Knowledge Discovery by Reversing Inductive Knowledge Representation

In a very basic sense, the aim of knowledge discovery is to reveal structures of knowledge which can be seen as being represented by structural relationships. In this paper, we make this notion more precise and present a method how to extract structural information from statistical data. There are two key ideas underlying our approach: First, knowledge discovery is understood as a process which...

Knowledge Discovery by Network Visualization

Hyperlinks among webpages are very important information and are widely used for webpage clustering and webpage ranking. With the explosive growth in the number of webpages available online, the exploration of hyperlinks among webpages becomes a very challenging problem. Information visualization provides an effective way of visualizing hyperlinks and can help users gain insights into the relat...

Designing an Ontology for Knowledge Discovery in Iran’s Vaccine

Ontology is a requirement engineering product and the key to knowledge discovery. It includes the terminology to describe a set of facts, assumptions, and relations with which the detailed meanings of vocabularies among communities can be determined. This is a qualitative content analysis research. This study has made use of ontology for the first time to discover the knowledge of vaccine in Ir...