Urban area function zoning based on user relationships in location-based social networks
dc.contributor.author | Hao, F | |
dc.contributor.author | Zhang, J | |
dc.contributor.author | Duan, Z | |
dc.contributor.author | Zhao, L | |
dc.contributor.author | Guo, L | |
dc.contributor.author | Park, DS | |
dc.date.accessioned | 2020-07-09T12:38:29Z | |
dc.date.issued | 2020-01-29 | |
dc.description.abstract | With advanced development of Internet communication and ubiquitous computing, Social Networks are providing an important information channel for smart city construction. Therefore, analyzing Location-based Social Network is a very valuable work in achieving reasonable urban zoning. In Social Networks, a main purpose of prestige assessment is to extract influential users who are regarded as the key nodes for community detection from Onine Social Networks (OSNs). However, social relationships of users are rarely used to evaluate the popularity of physical locations and zone physical locations. In order to achieve urban area function zoning by evaluating the prestige of geographic regions based on user relationships in Location based Social Networks (LBSNs), this paper proposes a Prestige Density-Based Spatial Clustering of Applications with Noise algorithm (P-DBSCAN) by improving the existing DBSCAN algorithm. Specifically, the algorithm first calculates the centrality of users in the social network, and then converts the centrality of users into the location-centrality through the users' check-in data. After the centrality of each location is obtained, the discrete locations are clustered according to four constraints of the given radius. After clustering, the result of urban area function zoning can be achieved. Extensive experiments are conducted for demonstrating the effectiveness of our proposed algorithm in this paper. In addition, the visualization results reveal the correctness of our proposed approach. | en_GB |
dc.description.sponsorship | National Natural Science Foundation of China | en_GB |
dc.description.sponsorship | European Union Horizon 2020 | en_GB |
dc.description.sponsorship | Natural Science Basic Research Plan in Shaanxi Province of China | en_GB |
dc.description.sponsorship | Fund Program for the Scientific Activities of Selected Returned Overseas Professionals in Shaanxi Province | en_GB |
dc.description.sponsorship | Ministry of Science and ICT (MSIT), South Korea | en_GB |
dc.description.sponsorship | National Research Foundation of Korea | en_GB |
dc.identifier.citation | Vol. 8, pp. 23487 - 23495 | en_GB |
dc.identifier.doi | 10.1109/ACCESS.2020.2970192 | |
dc.identifier.grantnumber | 61702317 | en_GB |
dc.identifier.grantnumber | H2020-MSCA-IF-2018-840922 | en_GB |
dc.identifier.grantnumber | 2019JM-379 | en_GB |
dc.identifier.grantnumber | 2017024 | en_GB |
dc.identifier.grantnumber | IITP-2019-2014-1-00720 | en_GB |
dc.identifier.grantnumber | 2017R1A2B1008421 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/121859 | |
dc.language.iso | en | en_GB |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_GB |
dc.rights | Open access. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/ | en_GB |
dc.subject | Social networking (online) | en_GB |
dc.subject | Clustering algorithms | en_GB |
dc.subject | Urban areas | en_GB |
dc.subject | STEM | en_GB |
dc.subject | Computer science | en_GB |
dc.subject | Data mining | en_GB |
dc.subject | Mobile handsets | en_GB |
dc.title | Urban area function zoning based on user relationships in location-based social networks | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2020-07-09T12:38:29Z | |
dc.description | This is the final version. Available on open access from IEEE via the DOI in this record | en_GB |
dc.identifier.eissn | 2169-3536 | |
dc.identifier.journal | IEEE Access | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2020-01-13 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2020-01-13 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2020-07-09T12:34:13Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2020-07-09T12:38:34Z | |
refterms.panel | B | en_GB |
refterms.depositException | publishedGoldOA |
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Except where otherwise noted, this item's licence is described as Open access. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/