标题：A New Method Based on Association Rules Mining and Geo-filter for Mining Spatial Association Knowledge

作者：Liu, YL (Liu, Yaolin); Xie, P (Xie, Peng); He, QS (He, Qingsong); Zhao, X (Zhao, Xiang); Wei, XJ (Wei, Xiaojian); Tan, RH (Tan, Ronghui)

来源出版物：CHINESE GEOGRAPHICAL SCIENCE卷：27期：3页码：389-401 DOI：10.1007/s11769-017-0873-y 出版年：JUN 2017

摘要：Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results containing large number of redundant rules. In this paper, a new method named Geo-Filtered Association Rules Mining (GFARM) is proposed to effectively eliminate the redundant rules. An application of GFARM is performed as a case study in which association rules are discovered between building land distribution and potential driving factors in Wuhan, China from 1995 to 2015. Ten sets of regular sampling grids with different sizes are used for detecting the influence of multi-scales on GFARM. Results show that the proposed method can filter 50%-70% of redundant rules. GFARM is also successful in discovering spatial association pattern between building land distribution and driving factors.

入藏号：WOS:000404173000005

文献类型：Article

语种：English

作者关键词： data mining; association rules; rules spatial visualization; driving factors analysis; land use change

扩展关键词： PATTERNS; LAND; DISCOVERY; FRAMEWORK; DATASETS

通讯作者地址：Xie, P (reprint author), Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

电子邮件地址：xiepenggis@163.com

地址：

[Liu, Yaolin; Xie, Peng; He, Qingsong; Zhao, Xiang] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

[Liu, Yaolin] Wuhan Univ, Key Lab Geog Informat Syst, Minist Educ, Wuhan 430079, Peoples R China.

[Wei, Xiaojian] East China Inst Technol, Fac Geomat, Nanchang 330013, Jiangxi, Peoples R China.

[Tan, Ronghui] Tianjin Univ, Coll Management & Econ, Tianjin 300072, Peoples R China.

研究方向：Environmental Sciences & Ecology

ISSN：1002-0063

eISSN: 1993-064X

影响因子：1.154