基于E-Learning的数据挖掘系统的改进设计与实现

Improved design and implementation of data mining system based on E-Learning

受到用户数据复杂性和多变性的影响,传统数据挖掘系统往往难以精确掌控用户数据走向。为加强数据挖掘系统的挖掘精度与稳定性,提出基于E-Learning的数据挖掘系统。该系统包括E-Learning编辑服务器和数据处理体系,ELearning编辑服务器由准备模块、展示模块和生成模块构成。准备模块为不了解E-Learning数据挖掘系统的用户提供帮助,将挖掘出的用户行为数据传递给展示模块,经展示模块对用户数据进行控制、筛选和解析并传输到生成模块与知识库,生成模块对挖掘出的用户数据进行个性化定制。数据处理体系利用数据挖掘查询语言进行数据查找与解析,将解析后的数据保存于知识库,并将数据传回E-Learning编辑服务器进行循环使用。软件设计中,给出通过数据挖掘查询语言衡量用户兴趣点,对知识库进行数据的多样性非标准挖掘过程。实验结果表明,所提方法拥有较高的挖掘准确度与稳定性。

With the influence of user data complexity and variability,it is often difficult for the traditional data mining system to control the trend of user data precisely. To strengthen the mining accuracy and stability of the data mining system,a data mining system based on E-Learning is put forward. The system includes the E-Learning editing server and data processing system. The E-Learning editing server is composed of preparatory module,display module and generation module. The preparatory module is used to provide help for the users who don＇t understand E-Learning data mining system,to transit the mined user behavior data to the showing module,to control,screen and parse the user data through the showing module,and then to transfer it to the generation module and knowledge base. The generation module is adopted to execute the personalized customization of the mined user data. The data processing system is employed to carry out data search and analysis with the data mining query language,save the parsed data in the knowledge base,and transit the data back to the E-Learning editing server for recycling.In software design,the user interests measured by the data mining query language are given,and the diversity non-standard data mining process is conducted for knowledge base. The test results show that the proposed method has higher mining accuracy and stability.