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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.
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