Study On Techniques Of Mining Spatial Association Rules With Decision Attributes In GIS Database

Content:It is Tobler's first geographical rule that everythings have associations, the incident is always associated with incidents which took place nearby,and more close is the distance between place,more close is the associations. This rule pointed out that spatial dependence exists in spatial objects. Therefore, mining spatial association rules in GIS database is suggested. In this paper, mbr and plane sweep algorithm are used to compute neigbour relation between spatial objects. Besides,spatial relations between spatial objects are covered , if they are computed, it will cost much time and memory. To solve this problem, spatial relations are computed gradually from up to down according to concept hierarchic tree of spatial predication , until all of node are computed or cut. Spatial relation discriminant method is used to compute single node. Thus, spatial data is transformed into transaction data.As for mining association rules in the transation database, if a mining target is decided according to application domain, that's to say ,determine condition attributes and decision attributes ,then the work will have half effort and double results. Hence, this paper mainly studies the techniques on process and methods of mining association rules with decision attributes in GIS database.In the process of mining association rules, transaction data are divided firstly according to indiscernibility relation of attribute. On the basis of the first step, discernibility matrix is used to calculate absolute reduction and absolute reduction algorithm is designed in this paper. Mining multi-layer and multi_dimension association rules algorithm with decision attributes is also designed on the basis of equivalence of reduction attributes.