Research Of Personalized Learning System Based On Web

The development of Internet changed traditional education, and accelerated the appearance of the new educational pattern at the same time. Personalized learning is based on the combination of distance learning and personalized service. Because the user interest model is the foundation and the core of the personalized learning, this thesis mainly discussed how to construct and express user's interest model, meanwhile discussed the application how user's interest models perform in the personalized learning system. Firstly, this thesis analyzed the common methods and the basic technology of user interest expressing, and discussed the change of user long-term interest and short-term interest. Then established user's long-term interest model automatically through mining the pages and the behavior of user browsed based on Web mining. In order to enhance the precision of the user model expression, this thesis improved common mode based on the key word expression, and proposed a method based on the concept expression, which eliminated the semantic polysemy and the different meanings in the certain degree. Secondly, when dispatching the education resource based on established user interest model, proposed a method of web documents clustering based on mutual information through analyzing common methods of document clustering and researching mutual information theory. Finally, designed and explored the main function module of personalized learning system. And the experimental results indicate that this approach has better performance and validity.