A novel algorithm of weighted fuzzy spatial association rule mining (WFSARM) for wasteland reclamation. Issue 1 (2nd January 2018)

• Record Type: Journal Article
• Authors: Faridi, Mainaz; Verma, Seema; Mukherjee, Saurabh
• Is Part Of: Journal of information & optimization sciences. Volume 39:Issue 1(2018)
• Page Start: 195
• Page End: 211
• Publication Date: 2018-01-02
• Subjects: Weighted Fuzzy Spatial Association Rule Mining -- GIS -- Weight area score -- Faith -- Weighty itemsets -- Wasteland reclamation; 68W01; Electronic data processing -- Periodicals; Information science -- Periodicals; Mathematical optimization -- Periodicals; 519.6
• DOI: 10.1080/02522667.2017.1372920
• Languages: English
• ISSNs: 0252-2667

Abstract

Abstract: Wasteland reclamation is one of the ways in which the arable land can be increased. Weighted fuzzy spatial association rules could be used for associating wastelands with ground water and soil quality. The quality of wasteland, ground water and soil are used to provide weight. The association rules mined need to be further subjected to an interestingness measure that defines their utility. For the given challenge the authors propose a new algorithm for weighted fuzzy spatial association rule mining for wasteland reclamation (WFSARM) and ranking them on interestingness measures. Here, two new measures called faith and weight-area score are introduced. Multiple minimum faith thresholds are used for pruning of itemsets. The comparative analysis shows that the proposed algorithm is ef ficient and scalable and mines more number of rules as compared to Apriori algorithm. The results are viewed using GIS tool.