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earthquake data in spatial database include two typical types point and line feature, this paper propose an algorithm based on apriori for analysis spatial association pattern during point and line feature, and description algorithm process. since the algorithm is a probability-based mining algorithm, it apply in spatial database of seismic spatial database of Yunnan province china for analysis correlation of point and line pattern. The algorithm have certain significance for analysis spatial probabilistic and spatial reasoning for seismic spatial data. Keywords-spatial datamining ; seismic spatial data; probalistic I. INTRODUCTION Earthquake mechanisms and relevant principles suggest that the occurrence of the earthquake fault and geological activity showed great spatial correlation, which occurred mainly in the location of the earthquake fault zone adjacent geological activity or related areas. In spatial database, Geological active fault abstract as line feature, and earthquake source location abstract as point feature. apriori algorithm is association mining rule apply in database, and it extends to spatial database propose co-location algorithm. However, co-location algorithm is a common spatial data mining for point feature pattern and cannot apply in point and line features for seismic data(1)(2) . Seismic data in spatial include two typical types, point and line, in this paper we propose an algorithm based on apriori algorithm for analysis spatial association rule between point and line, description the process of algorithm and experiment algorithm on seismic spatial database of Yunnan province. Use this algorithm reveal association rule between point and line of seismic data and give probability relation of them. It have certain significance for analysis spatial probabilistic and spatial reasoning for seismic spatial database. II. SEISMIC SPATIAL DATA

An Apriori Based Algorithm Associated Point Line Pattern Applied in Seismic Spatial Data