Formal Concept Analysis for Digital Ecosystem
ICMLA '06 Proceedings of the 5th International Conference on Machine Learning and Applications
Expert Systems with Applications: An International Journal
An Approach for Web Services Composition Based on QoS and Discrete Particle Swarm Optimization
SNPD '07 Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02
Concept similarity in Formal Concept Analysis: An information content approach
Knowledge-Based Systems
Personalized web-based tutoring system based on fuzzy item response theory
Expert Systems with Applications: An International Journal
Using a style-based ant colony system for adaptive learning
Expert Systems with Applications: An International Journal
A blog-based dynamic learning map
Computers & Education
Expert Systems with Applications: An International Journal
Dynamic question generation system for web-based testing using particle swarm optimization
Expert Systems with Applications: An International Journal
An attribute-based ant colony system for adaptive learning object recommendation
Expert Systems with Applications: An International Journal
PSO-based single multiplicative neuron model for time series prediction
Expert Systems with Applications: An International Journal
QoL guaranteed adaptation and personalization in E-learning systems
IEEE Transactions on Education
An application of fuzzy information granulation in the emerging area of online sports
Expert Systems with Applications: An International Journal
Evolutionary computation approaches to the Curriculum Sequencing problem
Natural Computing: an international journal
Hi-index | 12.05 |
In the present learning cycle, new knowledge learning and known knowledge review are two important learning processes. Currently, the major attempts of e-Learning systems are devoted to promote the learners' learning efficiency in new knowledge learning, but only few in known knowledge review. Hence, this paper proposes the review course composition system which adopts the discrete particle swarm optimization to quickly pick the suitable materials, and can be customized in accordance with the learner's intention. Furthermore, the greed-like materials sequencing approach is also proposed to smoothe the reading order of the course. As a result, such a composition system satisfies the majority of learners with the customized review courses based on their needs.