基于数据挖掘的Web学习资源数据流处理技术

Web learning resource data stream processing technology based on data mining

为了更好地利用Web学习资源,针对当前Web学习资源流处理技术存在的不足,提出基于数据挖掘的Web学习资源数据流处理技术。首先分析Web学习资源流处理的研究进展,以及引起Web学习资源流处理效果不佳的因素;然后采用广度优先算法搜索网页,采集Web学习资源数据流,并采用贝叶斯网络算法挖掘数据流关联规则,寻找出网页内价值最高的信息,并利用弹性可伸缩机制实现学习资源数据流处理。实验结果表明,数据挖掘技术可以准确发现Web学习资源流的变化点,得到的Web学习资源数据流相关性较高,提高了学习资源数据流回调率,具有更高的实际应用价值。

In view of the shortcomings of the current processing technology of Web learning resource flow,a Web learning resource data flow processing technology based on data mining is proposed to make good use of the Web learning resources.The research progress of Web learning resource flow processing technology and the factors causing poor processing effect of Web learning resource flow are analyzed.The breadth⁃first search algorithm is used to search the webpage.The Web learning resource data flow is collected.The Bayesian network algorithm is used to mine the data flow association rules to find out the most valuable information in the webpage.The elastic and scalable mechanism is used to process data flow of learning resources.The experimental results show that the data mining technology can accurately find out the change points of Web learning resource flow,obtain high correlation of Web learning resource data flow,and improve the recall rate of learning resource data flow.Therefore,it has higher practical application value.