To improve the scalability of resources and ensure the effective sharing and utilization of online English resources, an online English resource integration algorithm based on high-dimensional mixed-attribute data mining is proposed. First, an integration structure based on high-dimensional mixed-attribute data mining is constructed. According to this structure, the characteristics of online English resources are extracted, and historical data mining is carried out in combination with the spatial distribution characteristics of resources. In this way, the spatial mapping function of features is established, and the optimal clustering center is designed according to the clustering and fusion structure of online English resources. At this node, the clustering and fusion of online English resources are carried out. According to the fusion results, the distribution structure model of online English resources is constructed, and the optimization research of the integration algorithm of online English resources is carried out. The experimental results show that the integration optimization efficiency of the proposed algorithm is 89%, and the packet loss rate is 0.19%. It has good integration performance, and can realize the integration of multi-channel and various forms of online English resources.

为了提高资源的可扩展性，保证在线英语资源的有效共享和利用，提出一种基于高维混合属性数据挖掘的在线英语资源整合算法。首先，构建了基于高维混合属性数据挖掘的集成结构。根据该结构，提取在线英语资源的特征，并结合资源的空间分布特征进行历史数据挖掘。这样就建立了特征的空间映射函数，并根据在线英语资源的聚类融合结构设计了最优聚类中心。在这个节点上，进行在线英语资源的聚类和融合。根据融合结果，构建在线英语资源分布结构模型，并对在线英语资源融合算法进行优化研究。实验结果表明，该算法的集成优化效率为89%，丢包率为0.19%。具有良好的集成性能，可以实现多渠道、多种形式的在线英语资源的集成。