SYSTEMS AND METHODS FOR CONTEXTUAL RECOMMENDATION OF LEARNING CONTENT

摘要

Systems and Methods for contextual recommendation of learning content based on various parameters and using probabilistic framework are provided. The recommendation system is a function of learner's profile, job context and learner's role wherein utility values are computed and combined for each of the learning content and compared to enable the system to recommend the most relevant learning content to the learner. The system further utilizes Bayesian reasoning model for otherwise inaccurately specified parameters to impart robustness and flexibility to the system.