At the same time, varying laws of support and confidence are studied while deducing new spatial association rules.
同时，推导了空间关联规则的支持度和可信度的变化规律。
This paper is focused on the methods of the construction of spatial transaction database, which is a crucial ste Pin the spatial association rules mining.
将空间数据库转换成空间事务数据库是空间关联规则挖掘过程的关键步骤。
Mining spatial association rules can be used to discover the specific spatial relationship between spatial predicate and non-spatial predicate in the spatial database.
空间关联规则挖掘可应用于发现空间数据库中大量空间谓词与非空间谓词之间的特定空间关系。
Spatial Association Rules is important information of implying in the data, this paper adopts method research Spatial Association Rules abstraction of message that data excavate.
空间关联规则是空间数据中重要的隐含信息，本文采用数据挖掘的方法研究空间关联规则信息的提取。
The spatial dependence in data mining is normally represented by spatial association rules, which provide the critical information in assessing spatial correlations in large spatial databases.
空间数据挖掘中所依赖的空间相关性是由空间关联规则描述的。
The way of generating frequent candidate a nd pruning technology are difficult technical problem when prenest traditional association rules mining algorithm is used to spatial data mining.
现有的传统关联规则挖掘算法构建频繁候选项的方式和修剪技术是其应用于空间数据挖掘的技术难题。
The way of generating frequent candidate a nd pruning technology are difficult technical problem when prenest traditional association rules mining algorithm is used to spatial data mining.
现有的传统关联规则挖掘算法构建频繁候选项的方式和修剪技术是其应用于空间数据挖掘的技术难题。
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