Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Logic based modeling and analysis of workflows
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Leading with Knowledge: The Nature of Competition in the 21st Century
Leading with Knowledge: The Nature of Competition in the 21st Century
On building workflow models for flexible processes
ADC '02 Proceedings of the 13th Australasian database conference - Volume 5
Virtual Corporate Universities: A Matrix of Knowledge and Learning for the New Digital Dawn
Virtual Corporate Universities: A Matrix of Knowledge and Learning for the New Digital Dawn
Authoring of learning styles in adaptive hypermedia: problems and solutions
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Adaptive Instructional Planning Using Ontologies
ICALT '04 Proceedings of the IEEE International Conference on Advanced Learning Technologies
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As the demand of corporate learning is growing, there is a need to develop suitable courseware for them. However, a major difference of systems being used in schools and corporations is that learner backgrounds are highly diversified in corporate learning. Very often, learners with different backgrounds would prefer different learning sequences. In this paper, the discovery of effective learning paths for corporate learners is proposed. Frequent sequences are extracted from previous learners' logs and be used to build a learning flow model of which the relationships between content materials are formulated by the use of conditional probability.