摘要： 提出了一个新型的基于大型数据流的实时处理模型,其处理模式主要是以实时存储和实时分析为主要目标,利用回归、聚类、实时分析等方法为数据流建立了一个完整的处理模型。该模型是对现有模型的完善和改进,从而在有限的存储空间中能切实可行地对快速的流数据做出实时响应。详细阐述了模型的框架建立和处理用户需求的过程与算法。

关键词: 回归, 聚类, 实时处理, 流数据挖掘

Abstract: A novel framework used to deal with the real-time data stream is proposed. Regression, clustering and real-time analysis are used tobuild an integrative architecture for the data stream and make the real-time storage and analysis feasible. Based on the improvement of the originalframework, the new framework makes it possible to real time respond the rapid data stream in the limit storage space. The detail process andarithmetic for constituting the framework and dealing with the users requirements are expatiated.

中图分类号: 

• TP311.52