A learner's style and profile recognition via fuzzy cognitive map

There is a crucial issue in adaptive educational hypermedia, concerning the machine's ability to recognize the learner's style and profile to the purpose of providing the learning material tailored to the learner's specific needs. In this paper an approach to this problem is presented, based on methodologies one can find in fuzzy logic and neural networks. The so-called fuzzy cognitive map becomes a powerful tool in this case, as it has been proved in other applications to. The reason, which leads to such approach, is mainly the observation of uncertainty in learner's profile description. Therefore, classes in any classification of learner's profile are considered as fuzzy sets and are represented as vertices of a fuzzy cognitive map.