{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T05:17:53Z","timestamp":1781587073215,"version":"3.54.5"},"reference-count":20,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2020,3,31]],"date-time":"2020-03-31T00:00:00Z","timestamp":1585612800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41871375"],"award-info":[{"award-number":["41871375"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018YFB2100700"],"award-info":[{"award-number":["2018YFB2100700"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Point of interest (POI) matching is critical but is the most technically difficult part of multi-source POI fusion. The accurate matching of POIs from different sources is important for the effective reuse of POI data. However, the existing research on POI matching usually adopts weak constraints, which leads to a low POI matching accuracy. To address the shortcomings of previous studies, this paper proposes a POI matching method with multiple determination constraints. First, according to various attributes (name, class, and spatial location), a new calculation model considering spatial topology, name role labeling, and bottom-up class constraints is established. In addition, the optimal threshold values corresponding to the different attribute constraints are determined. Second, according to the multiattribute constraint values and optimal thresholds, a constraint model with multiple strict determination constraints is proposed. Finally, actual POI data from Baidu Map and Gaode Map in Dongying city is used to validate the method. Comparing to the existing method, the accuracy and recall of the proposed method increase 0.3% and 7.1%, respectively. The experimental results demonstrate that the proposed POI matching method attains a high matching accuracy and high feasibility.<\/jats:p>","DOI":"10.3390\/ijgi9040214","type":"journal-article","created":{"date-parts":[[2020,3,31]],"date-time":"2020-03-31T10:29:38Z","timestamp":1585650578000},"page":"214","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Different Sourcing Point of Interest Matching Method Considering Multiple Constraints"],"prefix":"10.3390","volume":"9","author":[{"given":"Chengming","family":"Li","sequence":"first","affiliation":[{"name":"Chinese Academy of Surveying and mapping, Beijing 100830, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Liu","sequence":"additional","affiliation":[{"name":"Chinese Academy of Surveying and mapping, Beijing 100830, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaoxin","family":"Dai","sequence":"additional","affiliation":[{"name":"Chinese Academy of Surveying and mapping, Beijing 100830, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoli","family":"Liu","sequence":"additional","affiliation":[{"name":"Chinese Academy of Surveying and mapping, Beijing 100830, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,31]]},"reference":[{"key":"ref_1","first-page":"45","article-title":"Personalized Context-Aware Point of Interest Recommendation","volume":"36","author":"Aliannejadi","year":"2018","journal-title":"ACM Trans. Inf."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Huang, Y., Xiong, H., Leach, K., Zhang, Y., Chow, P., Fua, K., and Barnes, L.E. (2016, January 12\u201316). Assessing social anxiety using gps trajectories and point-of-interest data. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Heidelberg, Germany.","DOI":"10.1145\/2971648.2971761"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.compenvurbsys.2014.12.001","article-title":"Mining point-of-interest data from social networks for urban land use classification and disaggregation","volume":"53","author":"Jiang","year":"2015","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_4","first-page":"341","article-title":"Automated identification and characterization of parcels with OpenStreetMap and points of interest","volume":"43","author":"Liu","year":"2015","journal-title":"Environ. Plan. B Urban Anal. City Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"105","DOI":"10.3233\/WEB-180376","article-title":"A point of interest recommendation method using user similarity","volume":"16","author":"Zhang","year":"2018","journal-title":"Web Intell."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1080\/13658816.2016.1188930","article-title":"Similarity matching for integrating spatial information extracted from place descriptions","volume":"31","author":"Kim","year":"2016","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Lamprianidis, G., Skoutas, D., Papatheodorou, G., and Pfoser, D. (2014, January 4\u20137). Extraction, integration and analysis of crowdsourced points of interest from multiple web sources. Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information, Dallas, TX, USA.","DOI":"10.1145\/2676440.2676445"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Scheffler, T., Schirru, R., and Lehmann, P. (2012). Matching Points of Interest from Different Social Networking Sites, Springer.","DOI":"10.1007\/978-3-642-33347-7_24"},{"key":"ref_9","unstructured":"Hochmair, H., Juh\u00e1sz, L., and Cvetojevic, S. (2018, January 15\u201317). Data Quality of Points of Interest in Selected Mapping and Social Media Platforms. Proceedings of the LBS 2018: 14th International Conference on Location Based Services, Zurich, Switzerland."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Novack, T., Peters, R., and Zipf, A. (2018). Graph-Based Matching of Points-of-Interest from Collaborative Geo-Datasets. ISPRS Int. J. Geo Inf., 7.","DOI":"10.3390\/ijgi7030117"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Mckenzie, G., Janowicz, K., and Adams, B. (2013, January 5\u20138). Weighted multi\u2013attribute matching of user\u2013generated points of interest. Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Orlando, FL, USA.","DOI":"10.1145\/2525314.2525455"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"49","DOI":"10.14257\/astl.2014.45.10","article-title":"Organization and Retrieval Method of Multimodal Point of Interest Data Based on Geo-ontology","volume":"45","author":"Xia","year":"2014","journal-title":"Adv. Sci. Technol. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1080\/13658816.2013.830728","article-title":"Geometric-based approach for integrating vgi pois and road networks","volume":"28","author":"Yang","year":"2014","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_14","first-page":"111","article-title":"Multi-Source POI data fusion based on the spatial location information","volume":"44","author":"Zhang","year":"2014","journal-title":"Period. Ocean Univ. China"},{"key":"ref_15","first-page":"51","article-title":"Multi-source POI Duplication Detection Method in Map World Fujian Based on Word Segmentation","volume":"16","author":"Huang","year":"2018","journal-title":"Geospat. Inf."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"786","DOI":"10.1080\/13658816.2014.997238","article-title":"Pattern-mining approach for conflating crowdsourcing road networks with POIs","volume":"29","author":"Yang","year":"2015","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1080\/15230406.2014.880327","article-title":"A weighted multi\u2013attribute method for matching user\u2013generated Points of Interest","volume":"41","author":"Mckenzie","year":"2014","journal-title":"Cartogr. Geogr. Inf. Sci."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Li, L., Xing, X., Xia, H., and Huang, X. (2016). Entropy-Weighted Instance Matching Between Different Sourcing Points of Interest. Entropy, 18.","DOI":"10.3390\/e18020045"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Deng, Y., Luo, A., Liu, J., and Wang, Y. (2019). Point of Interest Matching between Different Geospatial Datasets. ISPRS Int. J. Geo Inf., 8.","DOI":"10.3390\/ijgi8100435"},{"key":"ref_20","first-page":"160","article-title":"An approach for spatial index of text information based on cosine similarity","volume":"32","author":"Zhang","year":"2005","journal-title":"Comput. Sci."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/4\/214\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:13:50Z","timestamp":1760174030000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/4\/214"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,31]]},"references-count":20,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2020,4]]}},"alternative-id":["ijgi9040214"],"URL":"https:\/\/doi.org\/10.3390\/ijgi9040214","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3,31]]}}}