The Study And Design Of Personalized Education System Based On Quantization Browsing Behavior

With the rapid development of global information, computer networking hasbecome a indispensable knowledge information sources, but with an accompanyingnetwork information infinite growth issue. This issue brings Information resourcesupply far greater than the demand for resources, which makes us have to find out asolution to seek out the required resources accurately and rapidly from the vast oceanof information. Therefore, personalized service have became a research hot spot in theinformation field.On the other hand, the learning process has usually been arranged in advancedby traditional education system, so the learning strategies and content obtained by thelearners are too curing and too onefold which can’t meet the personalized studydemands of learners. Therefore, personal services are also widely used in the modernteaching. Personalized education system analyzes the learning interests of differentlearners, provides the different teaching strategies and learning content for learners toachieve the desired effect of the individuation development.With the deep research on the theoretical knowledge and technology ofindividualization education, an education system based on the interest of learner isconstructed in this paper. It can be divided into three main modules: the studentinterest management module, the study resources management module andpersonalized recommendation module. The student interest management modulemainly achieves collection of students interest, construction of interest model, updateof interest model etc. As we know that accuracy of user interest model determines theaccuracy of the user information representation and directly influences the servicequality for the users. Therefore, this paper explicitly constructs students’ initialinterest model and implicitly updates interest model by tracking and collectingvarious browsing behaviors in the learning process, which improves the accuracy ofrecommendation results while reducing interference to the learning process. The studyresources management module mainly achieves the study document management andtext vector management etc. For each documents uploaded by teacher users, thismodule shall automatically pre-treat and construct the document vectors and finally use for personalized recommendation module. Personalized recommendation modulemainly achieves similarity comparison and sort recommend etc. That means thismodule will find out the documents that students might be interested in based on eachlearners’ interests and then recommend to students by scientific sorting method.At last, the paper proves the feasibility and suitability of this model throughperforming an experiment on the designed system, and obtaining the reasonablevalues of browsing behavior parameters with an adaptive method, and comparing withgeneral model through the experiment.