{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T21:13:30Z","timestamp":1785014010434,"version":"3.55.0"},"reference-count":58,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2020,4,4]],"date-time":"2020-04-04T00:00:00Z","timestamp":1585958400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2017M620885"],"award-info":[{"award-number":["2017M620885"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Support Project of High-level Teachers in Beijing Municipal Universities in the Period of 13th Five\u2013year Plan","award":["CIT&TCD201904037"],"award-info":[{"award-number":["CIT&TCD201904037"]}]},{"name":"R&amp;D Program of Beijing Municipal Education Commission","award":["KM202010011011"],"award-info":[{"award-number":["KM202010011011"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61802010"],"award-info":[{"award-number":["61802010"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>With the extensive use of digital signage, precise site selection is an urgent issue for digital signage enterprises and management agencies. This research aims to provide an accurate digital signage site-selection model that integrates the spatial characteristics of geographical location and multisource factor data and combines empirical location models with machine learning methods to recommend locations for digital signage. The outdoor commercial digital signage within the Sixth Ring Road area in Beijing was selected as an example and was combined with population census, average house prices, social network check-in data, the centrality of traffic networks, and point of interest (POI) facilities data as research data. The data were divided into 100\u20131000 m grids for digital signage site-selection modelling. The empirical approach of the improved Huff model was used to calculate the spatial accessibility of digital signage, and machine learning approaches such as back propagation neural network (BP neural networks) were used to calculate the potential location of digital signage. The site of digital signage to be deployed was obtained by overlay analysis. The result shows that the proposed method has a higher true positive rate and a lower false positive rate than the other three site selection models, which indicates that this method has higher accuracy for site selection. The site results show that areas suitable for digital signage are mainly distributed in Sanlitun, Wangfujing, Financial Street, Beijing West Railway Station, and along the main road network within the Sixth Ring Road. The research provides a reference for integrating geographical features and content data into the site-selection algorithm. It can effectively improve the accuracy and scientific nature of digital signage layouts and the efficiency of digital signage to a certain extent.<\/jats:p>","DOI":"10.3390\/ijgi9040217","type":"journal-article","created":{"date-parts":[[2020,4,6]],"date-time":"2020-04-06T05:05:13Z","timestamp":1586149513000},"page":"217","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Site Selection of Digital Signage in Beijing: A Combination of Machine Learning and an Empirical Approach"],"prefix":"10.3390","volume":"9","author":[{"given":"Yuxue","family":"Wang","sequence":"first","affiliation":[{"name":"Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Su","family":"Li","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5502-2974","authenticated-orcid":false,"given":"Xun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China"},{"name":"Key Laboratory of Resources Utilization and Environmental Remediation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4154-5969","authenticated-orcid":false,"given":"Dong","family":"Jiang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Resources Utilization and Environmental Remediation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengmeng","family":"Hao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Resources Utilization and Environmental Remediation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Zhou","sequence":"additional","affiliation":[{"name":"Institute of Earthquake Forecasting, China Earthquake Administration, Beijing 100036, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1177\/1550147716657926","article-title":"Performance analysis of smart digital signage system based on software-defined IoT and invisible image sensor communication","volume":"12","author":"Hossain","year":"2016","journal-title":"Int. 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