Abstract: Its getting more significant to recognize how to determine spatial knowledge naturally from spatial datasets with the rapid development and broad applications of the spatial dataset. Spatial co-location patterns speak to the rifts of peculiarities whose incidences are oftentimes speckled mutually in geographic space. It "s" hard to revelation co-location design in outlook of the immense compute of information brought by the incidences of spatial peculiarities. The existing system exploit order-clique-based methodology to mine the maximal co-location design which makes exploitation of the tree structure though with an exact end goal to build the ability of the methodology; the lattice structure is employed to mine the maximal co-location rather than the tree structure. The maximal co-location models is mined by the proposed calculation utilizing three noteworthy steps: The spatial neighbor connections lattice structure development and mining of maximal co-location design the implementation of the proposed figuring is assessment with real and synthetic dataset. The execution is calculated by the memory space, running time and the quantity of sequence needed for the proposed and the existing system. The execution study exhibits that the projected system is more efficient than that of the order-clique-based strategy.
P. Rubini and C. Gowri Shankar, 2016. Lattice Structure-Based Spatial Co-Location Pattern Mining Using Rect Search Algorithm. Asian Journal of Information Technology, 15: 4200-4212.