• Dushyant Singh

Data mining is described as the process of finding, analyzing, and sifting through vast quantities of data in order to uncover connections, patterns, or statistical correlations. SDM (Geographic Data Mining) is the process of extracting interesting, useful, and non-trivial patterns from massive spatial datasets. Due to the complexity of geographical data types, spatial connections, and spatial auto-correlation, finding interesting and meaningful patterns from spatial datasets must be more challenging than extracting the equivalent patterns from conventional numeric or categorical data. Emphasis was placed on the distinct characteristics that differentiate geographical data mining from traditional data mining, as well as the significant achievements of spatial data mining research. In precision agriculture, community planning, resource finding, and other fields, extracting intriguing patterns and rules from spatial information, such as remotely sensed images and related ground data, may be useful.

Cluster, Connection, Data, Information, Mining.

"A Review Paper on Data Mining", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.366-370, December-2018, Available :http://www.jetir.org/papers/JETIRFJ06076.pdf

"A Review Paper on Data Mining", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp366-370, December-2018, Available at : http://www.jetir.org/papers/JETIRFJ06076.pdf