Multi-Resolution Pruning Based Co-Location Identification In Spatial Data
Sruthi K Surendran, S. Dhamodaran · IOSR Journal of Computer Engineering · 2014
A co-location spatial pattern is a pattern of multiple groups which co-relates spatial features or events that are frequently located in same zone.Co-location pattern mining emphasizes overall analysis by manipulating the proportion of spatial features and other relevant information's.In this paper we are trying to remove the problem of co-location mining from the large data set.Data is generated from wide range of data sources that are available in geographical space.One method to mine the widely spread co-location is to compute the participation index in measuring the prevalence of the co-location.First option from the above said the measure is closely inter-related to cross function, which often used for measuring the statistical among various pair of spatial features.Second option focused on the property of anti-monotones which can be included for computational perspective efficiency.In this paper, we are trying to incorporate a novel multi-resolution pruning technique to address the problem of mining co-location data pattern with rare spatial features.