A Journey through the Spatial Data Mining and Geographic Knowledge Discovery Jungle

• Main Author: KAM, Tin Seong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2011
• Subjects: Business Analytics; Spatial Data Mining; Geographical Knowledge Discovery; Databases and Information Systems; Geographic Information Sciences
• Online Access: https://ink.library.smu.edu.sg/sis_research/1482
• Institution: Singapore Management University

Voluminous geospatially-referenced data have been, and continue to be, collected with modern data acquisition techniques such as global positioning systems (GPS), RFID, internet-based volunteered data, and smartphones. There is an urgent need for effective and efficient methods to extract unknown and unexpected information from geospatially-referenced data sets of unprecedentedly large size, high dimensionality, and complexity. Using powerful data discovery and robust visual analytics of JMP software from SAS Institute Inc., this presentation aims to bring spatial data mining and geographic knowledge discovery within the reach of business and IT professionals with little statistical training. An emphasis is placed on a paradigm for understanding complex and massive business data that is visual, intuitive, and interactive, rather than one that relies on convoluted logic, heavy mathematics or passive acceptance of results.