Spatial data mining using k means algorithm and find users having common interest using genetic algorithm

  Taruna Sehgal,  Er. Yogesh Kumar

Spatial Data Mining (SDM) is an important branch of data mining. With the large amount of spatial data stored in a Geographic Information System (GIS) spatial database, many knowledge and laws need to be mined. This paper presents the understanding of Geographical Information System (GIS) for analysing data using data mining techniques. Spatial Data Mining (SDM) technology has emerged as a new area for spatial data analysis. Geographical Information System (GIS) stores data collected from heterogeneous sources in varied formats in the form of geodatabases representing spatial features, with respect to latitude and longitudinal positions. The intent of this paper is to introduce with GIS, and spatial data mining, GIS and SDM tasks, issues and challenges, and role of spatial association rule mining in big data of GIS

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Unique Identification Number - IJEDR1903125
Page Number(s) - 722-728
Pubished in - Volume 7 | Issue 3 | September 2019
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Taruna Sehgal,  Er. Yogesh Kumar,   "Spatial data mining using k means algorithm and find users having common interest using genetic algorithm", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.7, Issue 3, pp.722-728, September 2019, Available at :http://www.ijedr.org/papers/IJEDR1903125.pdf