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…

This paper provides lessons learned and some unexpected transformations in the learning process when advanced collaboration technology was used to overcome limitations of a popular, existing collaboration technology. The activities pursued in these advanced undergraduate and graduate computer and information…

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 paper presents a case study illustrating a collaborative problem solving process in Virtual Communities of Practice. The process relies on the existence of an underlying shared knowledge base – a repository of resources, and is carried out collaboratively by…

Argumentation systems have substantially evolved in the past few years, resulting in adequate tools to model
some forms of common sense reasoning. This has sprung a new set of argument-based applications in diverse
areas.
In previous work, we defined how…

The aim of this work is to analyze the knowledge interchange on multi-agent systems using shared knowledge areas. The project involves the analysis and reformulation of some aspects of the Linda model, adding new model level features. This work proposes…

There are three kinds of uncertainty in the process of fish-disease diagnosis, such as randomicity, fuzzy and imperfection, which affect the veracity of fish-disease diagnostic conclusion. So, it is important to construct a fish-disease diagnostic model to effectively deal with…

Associating the pattern in text data with the pattern with time series data is a novel task. In this paper, an approach that utilizes the features of the time series data and domain knowledge is proposed and used to identify…

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…