基于改进型关联算法的门票分析系统设计与实现

Design and Implementation of Ticket Analysis System Based on New Association Rules

提出了一种加权的关联规则CWA priori算法,在数据挖掘过程中,充分利用决策属性在挖掘中的作用,清洗掉数据源中无价值或价值较小的记录,从而达到节省程序运行时间和空间的目的。给出了CWA priori算法的描述,开发设计了基于该算法的A S-M in ing门票分析系统,该系统在项目单位正常运行使用。实践证明:发现的知识模式对公司的门票销售决策具有一定的实用参考价值,同时在节省程序运行资源方面也取得了良好的效果。

This paper introduces a weighted association rule algorithm CWApriori. During the data mining process, we make full use of the decision property to delete trivial or useless records in order to decrease run time and space. Also we design and implement ticket analysis system AS-Mining based on CWApriori, and this system is running normally in practice. Experiments prove that the system has a certain practical value, and obtains good effect in saving resources.