Big Data is being touted as the next big thing arousing technical challenges that confront
both academic research communities and commercial IT deployment. The root sources of …

Learning from non-stationary environments is a very popular research topic. There already
exist algorithms that deal with the concept drift problem. Among them there are online or …

Abstract Knowledge discovery in academic institution becomes more critical and crucial in
terms of identifying the student's performance. In the extraction of actionable knowledge from …

The process of learning can be improved with proper and timely feedback. This paper
proposes a system that provides feedback for both teacher and student using concept-based …

The ability of a classifier to take on new information and classes by evolving the classifier
without it having to be fully retrained is known as incremental learning. Incremental learning …

In most challenging applications learning algorithms acts in dynamic environments where
the data is collected over time. A desirable property of these algorithms is the ability of …

Due to rapid advancement in the field of computer communication there has been a lot of
research in development of Intelligent Tutoring System (ITS). However ITS fails to pinpoint …

We live in a dynamic world, where changes are a part of everyday life. When there is a shift
in data, the classification or prediction models need to be adaptive to the changes. In data …

This paper presents a learning classifier system ensemble for knowledge discovery from
incremental data. The new ensemble was designed with a two-level architecture to improve …

Class-incremental learning refers to the problem that the number of classes increases
dynamically in the training stage. In this paper, a method based on one class support vector …