Click-Stream Tracking For Chinese Learners Personalized Based On FP Grouping Algorithm

As the development of economy, science and culture is swift and violent in China, China is increasingly important in the world. In the language learning aspect, the demand of learning Chinese is rising continually, and the amount of people learning Chinese is increasing rapidly every year. Because the demand of learning Chinese is growing, popularize Chinese has become to a globalization trend.Network teaching is an important means of popularizing Chinese. However, there are many shortages of the recent network teaching whether in China or abroad. For example, deficient in the guide of new knowledge, lack the monitoring of learning process, and the model of instruction is too simplified. Therefore, individuation network teaching has become to the development trend of network teaching.Firstly, in this article, through the basic theory research of individuation study, learner model standard and learners model in common use, according to the learners model in common use and learner model standard, combine the characteristic of learners, such as age, gender, mother language background, study style and motivation etc., points out the basic model of Chinese language learner.Secondly, this article researches the basic theory of click stream tracking and FP An Algorithm for Frequent Patterns, and finds out the problem when using FP An Algorithm for Frequent Patterns build the tree mode, which needs a lot of memory space. In order to solve this problem, presents the new mode which through click stream data preprocessing mitigates the data volume during building FP-tree, thus achieve to optimize the FP algorithm.Thirdly, this article shows an idea which combine click stream tracking with FP An Algorithm for Frequent Patterns, excavating studying sequence of Chinese learners. Click stream tracking records study procedure of language learners, such as : Learners at what time visit which page, visiting frequency, type of this page etc. On the basis of the information and studying sequence, in accordance with the individuation index of Chinese language learners, divides Chinese language learners into groups.Finally, through experiment verifies that FP click stream tracking could achieve Chinese language learners personalized algorithm, projects, describes, and evaluates the algorithm. By survey 120 students about the satisfaction of system grouping strategy, depend on the questionnaire survey to evaluate and analyzes the algorithm.This article by tracks learning procedure of Chinese language learner, to achieve the aim which personalized to grouping Chinese language learners, research learners model, click stream tracking and FP An Algorithm for Frequent Patterns. According to the characteristics of Chinese language learners to present the individuation index of grouping Chinese language learners, efficiently combine click stream tracking with FP An Algorithm for Frequent Patterns. Not only solve the problem which appeared by using FP An Algorithm for Frequent Patterns to building tree, but also improve the reliability of grouping Chinese language learners.