大型数据库系统中一种新的属性依赖尺度
A New Scale for Attribute Dependency in Large Database Systems
摘要：
以数据为中心的大型应用程序具有不同的属性。在现代，绝大多数以数据为中心的大型应用程序都基于关系模型。数据库是表的集合，每个表都由许多属性组成。数据通常通过SQL查询访问。可以针对不同类型的优化来分析正在执行的查询。基于查询集合中不同属性的分析可以指导数据库管理员提高查询执行速度。在这种情况下，一个更好的模型将有助于预测即将到来的查询集的性质。一个有效的预测模型将指导数据库、数据仓库、数据采掘等不同的应用。建议的规模是建立在一些概率分析的基础上使用的属性在不同的查询。因此，该方法的目的是根据当前使用情况预测属性的未来使用情况。
英文摘要：
Large, data centric applications are characterized by its different attributes. In modern day, a huge majority of the large data centric applications are based on relational model. The databases are collection of tables and every table consists of numbers of attributes. The data is accessed typically through SQL queries. The queries that are being executed could be analyzed for different types of optimizations. Analysis based on different attributes used in a set of query would guide the database administrators to enhance the speed of query execution. A better model in this context would help in predicting the nature of upcoming query set. An effective prediction model would guide in different applications of database, data warehouse, data mining etc. In this paper, a numeric scale has been proposed to enumerate the strength of associations between independent data attributes. The proposed scale is built based on some probabilistic analysis of the usage of the attributes in different queries. Thus this methodology aims to predict future usage of attributes based on the current usage.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
