公开(公告)号：US5946683A

公开(公告)日：1999-08-31

申请号：US977878

申请日：1997-11-25

申请人： Rajeev Rastogi ,  Kyuseok Shim

发明人： Rajeev Rastogi ,  Kyuseok Shim

IPC分类号： G06F17/30

CPC分类号： G06F17/3061 ,  Y10S707/99931 ,  Y10S707/99932 ,  Y10S707/99933 ,  Y10S707/99935 ,  Y10S707/99936

摘要： In a data processing system, association rules are used to determine correlations of attributes of collected data, thereby extracting insightful information therefrom. In solving an optimized association rule problem where multiple instantiations for at least one uninstantiated attribute are required, unlike prior art, not all possible instantiations are considered to realize an optimized set of instantiations. Rather, using inventive pruning techniques, only selected instantiations need to be considered to realize same. In accordance with the invention, instantiations are assigned weights and are subject to pruning in an order dependent upon their weight. The weighted instantiations are tested based on selected criteria to identify, for example, those instantiations, consideration of which for the optimized set would be redundant in view of other instantiations to be considered. The identified instantiations are disregarded to increase the efficiency of determining the optimized set.

摘要翻译： 在数据处理系统中，使用关联规则来确定收集的数据的属性的相关性，从而从中提取有见识的信息。 在解决优化的关联规则问题中，其中需要至少一个未启动属性的多个实例化，与现有技术不同，并不是所有可能的实例被认为实现优化的一组实例。 相反，使用创造性的修剪技术，仅需要考虑选择的实例化才能实现。 根据本发明，实例化被赋予权重，并且以取决于它们的重量的顺序进行修剪。 基于所选择的标准来测试加权实例，以识别例如那些实例，考虑到要考虑的其他实例化，对于优化集合的考虑将是多余的。 识别的实例被忽略以提高确定优化集合的效率。