The Research On Web Usage Mining And Its Application To Personalized Learning System

Data mining is aiming at finding effective, innovative and comprehensive model within a huge amount of data. Web usage mining is the application of data mining to web usage data, whose main task is to survey users' browsing behavior, find out users' interest degree for web pages so as to improve web sites' structure and provide personalized service.The main content of this thesis includes:(1) web usage mining's features, method and related technology; (2)analysis the weakness of current data collecting technology and bring forward a integrated method of obtaining users' browsing information; (3) discussion of web visiting serial model method of mining based on graphic structure; (4) personalized recommending algorithm based on the combination of content filter and synchronization filter; (5)another part of this thesis elaborates the application of web usage mining on distance learning system to comprehend learners' learning pace, interests and needs in order to development personalized learning model and E-learning system.The main characteristics: the recommendation algorithm-based content filtering and collaborative filtering algorithm combined with the recommendation; website in the traditional learning modules into a personalized recommendation, the more modern individualized educational philosophy.