太阳成8722(中国)有限公司-GREEN NO.1

标题: Understanding the spatial dimension of natural language by measuring the spatial semantic similarity of words through a scalable geospatial context window

作者: Wang, BZ (Wang, Bozhi); Fei, T (Fei, Teng); Kang, YH (Kang, Yuhao); Li, M (Li, Meng); Du, QY (Du, Qingyun); Han, M (Han, Meng); Dong, N (Dong, Ning)

来源出版物: PLOS ONE  卷: 15  期: 7  文献号: e0236347  DOI: 10.1371/journal.pone.0236347  出版年: JUL 23 2020  

摘要: Measuring the semantic similarity between words is important for natural language processing tasks. The traditional models of semantic similarity perform well in most cases, but when dealing with words that involve geographical context, spatial semantics of implied spatial information are rarely preserved. Geographic information retrieval (GIR) methods have focused on this issue; however, they sometimes fail to solve the problem because the spatial and textual similarities of words are considered and calculated separately. In this paper, from the perspective of spatial context, we consider the two parts as a whole-spatial context semantics, and we propose a method that measures spatial semantic similarity using a sliding geospatial context window for geo-tagged words. The proposed method was first validated with a set of simulated data and then applied to a real-world dataset from Flickr. As a result, a spatial semantic similarity model at different scales is presented. We believe this model is a necessary supplement for traditional textual-language semantic analyses of words obtained by word-embedding technologies. This study has the potential to improve the quality of recommendation systems by considering relevant spatial context semantics, and benefits linguistic semantic research by emphasising the spatial cognition among words.

入藏号: WOS:000575913700078

PubMed ID: 32702022

语言: English

文献类型: Article

KeyWords Plus: INFORMATION-RETRIEVAL; SEARCH

地址: [Wang, Bozhi; Fei, Teng; Li, Meng; Du, Qingyun] Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China.

[Kang, Yuhao] Univ Wisconsin, Dept Geog, Geospatial Data Sci Lab, Madison, WI 53706 USA.

[Han, Meng; Dong, Ning] State Grid Beijing Elect Power Co, Beijing, Peoples R China.

通讯作者地址: Fei, T; Du, QY (通讯作者)，Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China.

电子邮件地址: feiteng@whu.edu.cn; qydu@whu.edu.cn

影响因子：2.74