Research On Sequential Patterns Mining In Self-Adaptive Learning System

According to the development of computer and network technique ,it is a age of information and economy, people is changing their ways of lives by the application of information technology in each field .The development of distance education is facing a challenge. As the traditional form of a single long-distance education, only pay attention to the neglect of the school, teaching poor interaction between the two sides, have been far from meeting the needs of learners. Learner-centred learning more and more attention from education researchers. How to properly deal with learners in self-learning network problems encountered in the network is a measure of the key study results.In order to solve the problems of Distance Education, education researchers made use of adaptive learning system to resolve this problem. Use of adaptive learning systems, computer systems as the role of teachers and learners to provide personalized for the independent learning environment. To achieve this function, we must first obtain learner characteristics. According to Learner characteristics can be different from the teaching content, teaching strategy ,to provide for different students of different teaching. Learner's characteristics is an important part in self-adaptive learning system.Analysis of learners in this paper from the theoretical study and analysis system to achieve learner characteristics of both domestic and international study of the current status, is the adaptive learning system in the framework structure, focus on the adaptive learning system in the characteristics of learners Model. Analysis of the main characteristics of the learner is ready to study and understanding of learners and their learning style activities. Understanding of learners study habits, analysis of its study methods, assess learning, learning to identify the best learning time, provide the best combination of courses, the final formulation suitable for learners of learning courses, such a personalized learning system Learning to stimulate the enthusiasm of learners and learning interest.Learner characteristics personalized study mining is actually a streaming data mining. At present streaming data mining is the main mode of mining sequence pattern mining. In this paper, sequential pattern mining AprioriAll algorithms have been studied, AprioriAll algorithm for the shortcomings, take an improved algorithm. Improved algorithm in the database by reducing the number of sequence set to improve the efficiency of algorithms. The algorithm can delete sequence database of the unfrequent sequence and smaller the length of sequence than k. This sequence set in scanning the candidate with the support of time, can be reduced in the database scanning the records of a few, reduce the burden systems, improve the efficiency of the algorithm.