A New Approach to Mine Frequent Pattern in Spatial Database Using TFP-Tree
Today there are several skilled algorithms to mine frequent patterns. Frequent item set mining provides the associations and correlations among items in large transactional or relational database. In this paper a new approach to mine frequent pattern in spatial database using TFP-tree is proposed. The proposed approach generates a TFP-tree that specifies the generations of frequent patterns. The authors' analysis approach generates maximal frequent patterns and performs only minimal generalizations of frequent candidate sets. Spatial database provisions a large amount of space related data, like as maps, preprocessed remote sensing or medical imaging, and VLSI chip lay out data. In different fields, there is a need to manage geometric, geographic, or spatial data.