Spatial Association Rule Mining Techniques Applied Research

The development of science and technology is so rapid that the data is no longer difficult to obtain, and the development led to an explosion of data. The whole world scientists are attracted by the problem which is how to use data effectively to provide better service of human society. In order to solve this question, two new technologies, Spatial data mining and knowledge discovery(SDMKD) and geographic information system(GIS),were created. GIS is an information system which is emphasizing the collection and management of information, another one emphasize information analysis and processing. Use the technology of SDMKD founding information which is implicit, valuable and could help people to make decision from GIS database. Through this way of integrating, people are able to work out the problem about how to use data effectively, and to avoid the situation of data explosion get worsening.In this paper, research the primary issue of mining spatial association rule in spatial data mining and knowledge discovery, and expound the theory including:spatial data mining and knowledge discovery concepts framework, the type of knowledge to be mined, mining methods. Then, studied from the concept of spatial data pretreatment, composition, commonly methods and discussing the rough set theory based on spatial data preprocessing methods.Later, discuss in-depth the spatial association rules and association rules.Then study the Apriori algorithm that use for mining spatial association rule.Finally, pick up the traffic violations data from the traffic database and put it into the Apriori algorithm, get a lot of. traffic violations association rule,Through explaining some of them,find the solution of many traffic question submitted by traffic violations association rule. It is proved that Apriori algorithm could be use for mining traffic violations association rule and can supply suggests to support the decision of management in traffic.