{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T04:39:35Z","timestamp":1772771975258,"version":"3.50.1"},"reference-count":42,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,3,3]],"date-time":"2020-03-03T00:00:00Z","timestamp":1583193600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources, Shenzhen, PR China","award":["KF-2018-03-009"],"award-info":[{"award-number":["KF-2018-03-009"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41901325"],"award-info":[{"award-number":["41901325"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Georeferencing by place names (known as toponyms) is the most common way of associating textual information with geographic locations. While computers use numeric coordinates (such as longitude-latitude pairs) to represent places, people generally refer to places via their toponyms. Query by toponym is an effective way to find information about a geographic area. However, segmenting and parsing textual addresses to extract local toponyms is a difficult task in the geocoding field, especially in China. In this paper, a local spatial context-based framework is proposed to extract local toponyms and segment Chinese textual addresses. We collect urban points of interest (POIs) as an input data source; in this dataset, the textual address and geospatial position coordinates correspond at a one-to-one basis and can be easily used to explore the spatial distribution of local toponyms. The proposed framework involves two steps: address element identification and local toponym extraction. The first step identifies as many address element candidates as possible from a continuous string of textual addresses for each urban POI. The second step focuses on merging neighboring candidate pairs into local toponyms. A series of experiments are conducted to determine the thresholds for local toponym extraction based on precision-recall curves. Finally, we evaluate our framework by comparing its performance with three well-known Chinese word segmentation models. The comparative experimental results demonstrate that our framework achieves a better performance than do other models.<\/jats:p>","DOI":"10.3390\/ijgi9030147","type":"journal-article","created":{"date-parts":[[2020,3,3]],"date-time":"2020-03-03T13:06:23Z","timestamp":1583240783000},"page":"147","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Spatial Context-Based Local Toponym Extraction and Chinese Textual Address Segmentation from Urban POI Data"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6340-7452","authenticated-orcid":false,"given":"Xi","family":"Kuai","sequence":"first","affiliation":[{"name":"Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Renzhong","family":"Guo","sequence":"additional","affiliation":[{"name":"Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhijun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Tianjin Institute of Surveying and Mapping, Changling Road, Tianjin 300381, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Biao","family":"He","sequence":"additional","affiliation":[{"name":"Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518061, China"},{"name":"Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources, Shenzhen 518034, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhigang","family":"Zhao","sequence":"additional","affiliation":[{"name":"Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Han","family":"Guo","sequence":"additional","affiliation":[{"name":"Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources, Shenzhen 518034, China"},{"name":"Shenzhen Research Center of Digital City Engineering, Shenzhen 518034, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1081","DOI":"10.1080\/13658810903289478","article-title":"Comparative evaluation and analysis of online geocoding services","volume":"24","author":"Roongpiboonsopit","year":"2010","journal-title":"Int. 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