Personalized intelligent question answering algorithm in e-learning

A personalized intelligent question answering algorithm is put up, which takes learners´ personality into account based on learners´ information. By introducing principal component analysis, the algorithm got comprehensive variables, and constructed the learner model. Subsequently, the paper analyzed how to integrate the learner´s characteristic and his question using harmony theory to dynamically produce a question model. Using the question model, this algorithm obtained the parameters of answer depth and presentation pattern adapted to the learner´s personality. Finally, according to parameters, personalized answer was matched for the learner by the application of adaptive neuron-fuzzy inference system (ANFIS). For that reason, the personalized intelligent question answering algorithm is able to make learners understand the answer better, and guarantee the efficiency of intelligent question answering.