The Research And Implementation Of The Sequential Pattern Mining Algorithm Base On The Learners` Behavior

With the rapid development of Chinese economic and the increase of Chinese national strength, the cultural exchanges between China and the world in political, economic become more frequent, the number of people learning Chinese increases all over the world, especially in Northeast Asia. Japan and ROK students in China accounted for 43% of the total number of students, and there are 39 Confucius Institutes accounting for 55% of the total number reached in the two countries. Since the constraints of geography and resources, traditional teaching has been unable to meet the rapid development of foreign language, thus the establishment of foreign language teaching platform has become an urgent task.Online teaching from the traditional teaching time and geographical factors, the foreign language teaching has inherent advantages, the traditional Chinese teaching complement. However, online teaching has its limitations, the current e-learning platforms such problems exist, such as learning content can not be rational and reasonable will be organized, but by simply stacking and a list of learning content, so that different learning backgrounds difficult to distinguish which part of the learner is suitable for their own learning content, online teaching has seriously affected the results.The rigid form of network teaching platform, the lack of interaction, not based on the individual circumstances of learners on the adjustment of teaching content. For different learners, their age, motivation, cultural background, experience, background and interest in learning all of their actions have a deep impact, how to act for different learners, for learners to design a different look for additional learning content important.Behavior of individual learners based learning system has a certain intelligence, behavior through judgments of learners to understand the learner's interest in preference, and through analysis of past and comparing the learner behavior to recommend for learners appropriate learning sequences, providing teaching materials for their learning, and truly allow individual learners of Chinese language teaching. The innovation of this article:(1) of the sequence mining algorithm based on the learner model. Learner model to learners specific attributes, the system model in accordance with the learner to understand the behavior of the learner, the learner model for algorithm design and system implementation of a guiding role.(2) The learner behavior based sequence mining algorithms. Learners according to the established model of learner behavior tracking, based on learner behavior, by using the sequence mining algorithm to identify the potential relationship between courses, recommended courses of interest more in line with the learner. Firstly, understanding of international trends on the Chinese language teaching and the advantages of individualized teaching, Chinese language teaching through the study abroad Web site, suggestions for improvement, and the Research sequence mining algorithms were outlined.The second chapter describes the E-learning, sequence mining principles and theoretical basis of Chinese mining, emphasizing the learner's subjectivity and uniqueness, for the network to provide a theoretical basis for Chinese teaching. In the classification learning management system, management system for learning activities (LAMS) with the support of the demand for individualized teaching, the system records the behavior of the learner, and then digging through the behavior of learners to understand the learner's interest, as recommend appropriate learning sequence of the learner, personalized teaching needs. Then for E-Learning and personalized learning theory, study the foreign language teaching for learners model.The third chapter focuses on the learner model. First, analysis of learners standards and design principles, learner model based on typical characteristics of Chinese learners, including learners of basic information model for teachers to understand the student information, the level of model is suitable for Chinese learners in the initial polymerclass, interest in learning groups and learning sequence model for tracking student learning behavior, and tap for students interested in learning sequences. Learner model is the system design and system implementation of the theoretical basis for follow-up study, learners will have access to information modeling process and learners to do a detailed study.Chapter IV focuses on the behavior of learners based sequence mining algorithms.First, the concept of data mining, data mining focuses on the process a bit on the back of the learners to provide the basis for the modeling process. And then act based on learners to study the sequence mining algorithm, described in AprioriAll algorithm in the application of learning behavior, and the algorithm proposed improvement and assessment methods. Assessment on the one hand is the need to meet the minimum support and minimum confidence, exchange of experts identified by the algorithm with the least support and minimum confidence; the other hand, to test the accuracy of the algorithm. Then the framework of the teaching platform, the platform processes and information in the learner model acquisition methods. Chapter V summarizes the thesis work, the contribution of this paper and the proposed vision for the future.Future work:(1) During the public testing phase, with the increased number of the users, the system should collecte more data and needed to be test further and adjust.(2) We hope students from their own perspective could propose system solution.(3) Continue the research and improvement of the sequence mining algorithms. According to the methods described in the text, narrow the scope of the collection of candidate sequences Ck to improve the efficiency and accuracy of the algorithm. Improve the learner model and the evaluation method to make it more reasonable and perfect.