支撑交通管理综合信息平台的信息挖掘模型

An Information-Mining Model Supporting Traffic Management Integrated Information Platform

本文分别从结构化信息源和非结构化信息源两个角度探讨支撑交通管理综合信息平台的信息挖掘模型,提出利用粗糙集理论的基本原理,对于其属性约简进行改进。在保证原有属性不变的条件下,削减了冗余信息,并可实现基于数据库存储数据的动态数据挖掘模型,避免了将大量数据从数据库中基于主题倒入数据仓库的传统数据挖掘模式。通过上述算法,不仅提高了信息挖掘的效率,而且可以实时在线信息挖掘,相对于传统的挖掘模式,本文提出的方法更适用于当前基于网络的交通管理综合信息平台的实际应用。

An information-mining model supporting the traffic management integrated information platform was discussed from two aspects of structured or unstructured information sources. By using the relative rough set theory, the reduced property was improved in reducing the redundant information under the condition of guarantee of the model original functions. Then, the modified information-mining model can directly obtain information from the database otherwise data ware, and processes the real-time and on-line information mining with high effectiveness.