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.