{"id":"https://openalex.org/W3168096119","doi":"https://doi.org/10.1109/tits.2021.3083486","title":"MM-UrbanFAC: Urban Functional Area Classification Model Based on Multimodal Machine Learning","display_name":"MM-UrbanFAC: Urban Functional Area Classification Model Based on Multimodal Machine Learning","publication_year":2021,"publication_date":"2021-06-08","ids":{"openalex":"https://openalex.org/W3168096119","doi":"https://doi.org/10.1109/tits.2021.3083486","mag":"3168096119"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2021.3083486","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2021.3083486","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010774945","display_name":"Xiujuan Xu","orcid":"https://orcid.org/0000-0003-4175-4493"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiujuan Xu","raw_affiliation_strings":["School of Software Technology, Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian University of Technology, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0003-4175-4493","affiliations":[{"raw_affiliation_string":"School of Software Technology, Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087929961","display_name":"Yulin Bai","orcid":null},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yulin Bai","raw_affiliation_strings":["School of Software Technology, Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software Technology, Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100345691","display_name":"Yu Liu","orcid":"https://orcid.org/0000-0002-0016-2902"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Liu","raw_affiliation_strings":["School of Software Technology, Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software Technology, Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101749133","display_name":"Xiaowei Zhao","orcid":"https://orcid.org/0000-0001-9631-1177"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaowei Zhao","raw_affiliation_strings":["School of Software Technology, Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software Technology, Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086045501","display_name":"Yuzhi Sun","orcid":"https://orcid.org/0000-0002-1718-549X"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuzhi Sun","raw_affiliation_strings":["School of Software Technology, Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software Technology, Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I27357992"],"apc_list":null,"apc_paid":null,"fwci":1.7683,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.85554864,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"23","issue":"7","first_page":"8488","last_page":"8497"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9642000198364258,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14413","display_name":"Advanced Technologies in Various Fields","score":0.9534000158309937,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6929843425750732},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.6641115546226501},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.632249116897583},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6012758016586304},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5787983536720276},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5630556344985962},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.5284702181816101},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4935094118118286},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49226489663124084},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45544034242630005},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43437460064888},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4142204523086548},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4134286046028137}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6929843425750732},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.6641115546226501},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.632249116897583},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6012758016586304},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5787983536720276},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5630556344985962},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.5284702181816101},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4935094118118286},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49226489663124084},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45544034242630005},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43437460064888},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4142204523086548},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4134286046028137},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2021.3083486","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2021.3083486","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.8100000023841858}],"awards":[{"id":"https://openalex.org/G8164307142","display_name":null,"funder_award_id":"61702076","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8560178389","display_name":"\u591a\u5143\u6307\u6807\u89c6\u89d2\u4e0b\u4ea4\u4e92\u5f0f\u53ef\u89c6\u5316\u4e3b\u9898\u6316\u6398\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61672128","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W236257283","https://openalex.org/W1990444226","https://openalex.org/W1995952828","https://openalex.org/W2001052226","https://openalex.org/W2005292390","https://openalex.org/W2024177114","https://openalex.org/W2078917018","https://openalex.org/W2079672634","https://openalex.org/W2085893612","https://openalex.org/W2087072474","https://openalex.org/W2128254161","https://openalex.org/W2138972650","https://openalex.org/W2167917621","https://openalex.org/W2295598076","https://openalex.org/W2334092286","https://openalex.org/W2346792925","https://openalex.org/W2363459671","https://openalex.org/W2544770515","https://openalex.org/W2622263826","https://openalex.org/W2789758093","https://openalex.org/W2790369295","https://openalex.org/W2884721255","https://openalex.org/W2902240328","https://openalex.org/W2963901018","https://openalex.org/W6707612859","https://openalex.org/W6729341736","https://openalex.org/W6739622702","https://openalex.org/W6745609711"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W4386690025","https://openalex.org/W2885778889","https://openalex.org/W2766514146","https://openalex.org/W2885516856","https://openalex.org/W2073883415","https://openalex.org/W4289703016"],"abstract_inverted_index":{"Most":[0],"of":[1,5,26,44,62,70,79,81,91,116,131,152,163,184,187,195,206,221,248],"the":[2,27,65,68,74,86,92,113,121,128,140,150,157,170,174,181,191,201,210,219,229,238,246,258],"classification":[3,42,158],"methods":[4,72],"urban":[6,45,196,254,266,270],"functional":[7,46,197,255],"areas":[8,47],"nowadays":[9],"are":[10],"only":[11],"based":[12,48,142,172,232],"on":[13,49,143,173,233],"single":[14,227],"source":[15],"data":[16,31,61,130,208],"analysis":[17,202],"and":[18,29,59,77,84,88,103,111,119,155,203,251,257,269],"modeling,":[19],"which":[20],"can":[21,216,243,260],"not":[22],"make":[23],"full":[24],"use":[25,169],"multi-scale":[28],"multi-source":[30,117],"that":[32,213],"is":[33],"easy":[34],"to":[35,108,125,133,148,168,179,189],"obtain.":[36],"Therefore,":[37],"this":[38,241],"paper":[39],"proposed":[40],"a":[41,226],"model":[43,95,215,259],"multi-modal":[50,222],"machine":[51],"learning,":[52],"by":[53],"analyzing":[54],"regional":[55],"remote":[56],"sensing":[57],"images":[58],"behavior":[60,129],"visitors":[63],"in":[64],"area,":[66],"using":[67],"combination":[69],"supervised":[71],"extracted":[73],"deep-seated":[75],"features":[76,90,188,220],"relationships":[78],"kinds":[80],"data,":[82,118],"filtered":[83],"merged":[85],"overall":[87,114],"local":[89],"data.":[93,223],"The":[94],"used":[96,120],"dual":[97],"branch":[98],"neural":[99],"network":[100],"combining":[101],"SE-ResNeXt":[102],"Dual":[104],"Path":[105],"Network":[106],"(DPN)":[107],"automatically":[109],"mined":[110],"fused":[112],"characteristics":[115,151],"designed":[122],"feature":[123],"engineering":[124],"deeply":[126],"mine":[127],"users":[132],"obtain":[134,190],"more":[135],"association":[136],"information,":[137],"then":[138],"combined":[139],"algorithm":[141,171],"Gradient":[144,175],"Boosting":[145,176],"Decision":[146,177],"Tree":[147,178],"learn":[149,180],"different":[153,161,185],"levels":[154,162,186],"obtained":[156],"probability":[159,182],"for":[160,263],"features.":[164],"Finally,":[165],"we":[166],"continued":[167],"distribution":[183],"final":[192],"prediction":[193,239],"results":[194,211,247],"area":[198],"classification.":[199],"Through":[200],"experimental":[204],"verification":[205],"real":[207],"sets,":[209],"showed":[212],"MM-UrbanFAC":[214],"effectively":[217,244],"integrate":[218,245],"Compared":[224],"with":[225],"classifier,":[228],"integration":[230],"framework":[231],"gradient":[234],"lifting":[235],"tree":[236],"improved":[237],"performance,":[240],"method":[242],"multiple":[249],"models":[250],"accurately":[252],"classify":[253],"areas,":[256],"provide":[261],"reference":[262],"tourism":[264],"recommendation,":[265],"land":[267],"planning":[268],"construction.":[271]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}