随着数据挖掘技术的兴起,各种应用于关联规则挖掘的算法也逐渐被关注.在数据库中除了能对数据的进行录入、查询、统计等简单功能应用,也能帮助用户发现大量数据中存在的各种有用的信息以及数据之间的关联性,帮助用户分析出其中有价值的信息,从而实现其中的商业价值.关联规则是数据挖掘领域的一个重要研究分支,其经典算法-Aprior算法被广泛采用,本文针对Aprior算法的局限性,将遗传算法应用在关联规则数据挖掘中进行分析并以某高校新生入学调查表中数据为例,挖掘出学校的环境、就业情况、校园社团活动、食堂用餐标准等因素与学生生源地情况及学生中学水平之间的相关联系,可以帮助高校在招生咨询和宣传中有所侧重,对不同地区的学生采取不同的宣传方式和宣传内容,来进一步扩大学校的招生规模.%With the rise of data mining technology, various applied to association rule mining algorithms have gradually been con-cerned. In addition to the data in the database will be entry, query, statistics and other simple functional applications, but also to help users find the relevance of the presence of large amounts of data in a variety of useful information and data between, to help us-ers analyze the valuable information, in order to achieve one of the commercial value. Association rules is an important research branch of data mining, which is the classical algorithm-Aprior algorithms are widely used, the limitations of this article for Aprior algorithm, genetic algorithm in association rule data mining for analysis and survey of a university freshmen the data, for example, to dig out the relevant contact the school environment, employment, campus community activities, canteen standards and other fac-tors with students and student high school students to the situation between the level that can be focused on helping college admis-sions consulting and publicity for students in different regions to take a different form of publicity and promotional content, to fur-ther expand the enrollment of the school.
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