Research On E-learning User Feature Modeling With Incomplete Information And Its Application In Knowledge Recommendation

E-learning is widely used in the field of education, staff training, and customer service. With the improvement of service requirements of users, research and practice implement the personalized knowledge recommendation with user model as its base and core. However, customer service pay more attention convenient and fast, the method of information acquisition with higher user participation in education is not applicable. And due to the problem of information description and understanding of users, the system is hard to gain the relatively complete information, especially the personalized information about users feature. To solve this problem, based on the analysis of the application field, through processing incomplete information to obtain the user characteristics, and then build user feature model, and apply it in the personalized knowledge recommendation.Personalized knowledge recommendation focus on the match between other attributes and user preferences on the base of content match, so two relevant user features-knowledge level and cognitive style are chosen. The Bayesian discriminant method was used to measure the knowledge level, which avoid the large-scale test. And the Bayesian network is adopted to recognize cognitive style, it realized the probability expression of multiple style based on the existing classification of cognitive style. And then establish user feature model based on these two characteristics, and it is expressed with vector. Finally, the users feature model was introduced to e-learning personalized knowledge recommendation. It made the result more precise, improved its personalization, and is the necessary supplement and sublimation to the content recommendation. The research results will be used to help E-learning service provider implement more personalized knowledge recommendation strategy based on the incomplete information, improve user satisfaction and loyalty, and then to obtain competitive position in market competition.