标題: A points of interest matching method using a multivariate weighting function with gradient descent optimization

作者: Zhou, Y (Zhou, Yang); Wang, MJ (Wang, Mingjun); Zhang, C (Zhang, Chen); Ren, F (Ren, Fu); Ma, XY (Ma, Xiangyuan); Du, QY (Du, Qingyun)

來源出版物: TRANSACTIONS IN GIS DOI: 10.1111/tgis.12690 提前訪問日期: OCT 2020

摘要: Volunteered geographic information contains abundant valuable data, which can be applied to various spatiotemporal geographical analyses. While the useful information may be distributed in different, low-quality data sources, this issue can be solved by data integration. Generally, the primary task of integration is data matching. Unfortunately, due to the complexity and irregularities of multi-source data, existing studies have found it difficult to efficiently establish the correspondence between different sources. Therefore, we present a multi-stage method to match multi-source data using points of interest. A spatial filter is constructed to obtain candidate sets for geographical entities. The weights of non-spatial characteristics are examined by a machine learning-related algorithm with artificially labeled random samples. A case study on Fuzhou reveals that an average of 95% of instances are accurately matched. Thus, our study provides a novel solution for researchers who are engaged in data mining and related work to accurately match multi-source data via knowledge obtained by the idea and methods of machine learning.

入藏号: WOS:000575017100001

語言: English

文獻類型: Article; Early Access

地址: [Zhou, Yang; Wang, Mingjun; Zhang, Chen; Ren, Fu; Ma, Xiangyuan; Du, Qingyun] Wuhan Univ, Sch Resource & Environm Sci, 129 Luoyu Rd, Wuhan 430079, Peoples R China.

[Ren, Fu; Du, Qingyun] Wuhan Univ, Key Lab Geog Informat Syst, Minist Educ, Wuhan, Peoples R China.

通訊作者地址: Du, QY (通訊作者)，Wuhan Univ, Sch Resource & Environm Sci, 129 Luoyu Rd, Wuhan 430079, Peoples R China.

電子郵件地址: qydu@whu.edu.cn

影響因子：2.119