{"id":"https://openalex.org/W4312794196","doi":"https://doi.org/10.1109/tkde.2022.3220874","title":"Region Embedding With Intra and Inter-View Contrastive Learning","display_name":"Region Embedding With Intra and Inter-View Contrastive Learning","publication_year":2022,"publication_date":"2022-12-07","ids":{"openalex":"https://openalex.org/W4312794196","doi":"https://doi.org/10.1109/tkde.2022.3220874"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2022.3220874","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3220874","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","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/A5078032675","display_name":"Liang Zhang","orcid":"https://orcid.org/0000-0003-0905-9765"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Liang Zhang","raw_affiliation_strings":["Department of Computer Science, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044528555","display_name":"Cheng Long","orcid":"https://orcid.org/0000-0001-6806-8405"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Cheng Long","raw_affiliation_strings":["Department of Computer Science, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045198704","display_name":"Gao Cong","orcid":"https://orcid.org/0000-0002-4430-6373"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Gao Cong","raw_affiliation_strings":["Department of Computer Science, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5078032675"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":7.9481,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.97246144,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"35","issue":"9","first_page":"9031","last_page":"9036"},"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":0.9975000023841858,"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":0.9975000023841858,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9866999983787537,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10226","display_name":"Land Use and Ecosystem Services","score":0.9855999946594238,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.7389443516731262},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7142883539199829},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6798601150512695},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.6529961824417114},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6273559331893921},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5735822916030884},{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.5434257984161377},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5153753161430359},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.4581088721752167},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4416669011116028},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.386706680059433},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3809136748313904},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.37081217765808105},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14485052227973938}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7389443516731262},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7142883539199829},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6798601150512695},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.6529961824417114},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6273559331893921},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5735822916030884},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.5434257984161377},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5153753161430359},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.4581088721752167},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4416669011116028},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.386706680059433},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3809136748313904},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37081217765808105},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14485052227973938},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tkde.2022.3220874","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3220874","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"},{"id":"pmh:oai:dr.ntu.edu.sg:10356/172863","is_oa":false,"landing_page_url":"https://hdl.handle.net/10356/172863","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320327962","display_name":"Singapore Telecommunications Limited","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2071702404","https://openalex.org/W2149510050","https://openalex.org/W2768009948","https://openalex.org/W2785325870","https://openalex.org/W2807954821","https://openalex.org/W2892816441","https://openalex.org/W2901188091","https://openalex.org/W2903883820","https://openalex.org/W2940460948","https://openalex.org/W2944828972","https://openalex.org/W2952611035","https://openalex.org/W2964246847","https://openalex.org/W3005680577","https://openalex.org/W3027097765","https://openalex.org/W3034277777","https://openalex.org/W3094454579","https://openalex.org/W3102840236","https://openalex.org/W3122451732","https://openalex.org/W3126605250","https://openalex.org/W3159434472","https://openalex.org/W4200292294","https://openalex.org/W4223909865","https://openalex.org/W4312331995","https://openalex.org/W6747899497","https://openalex.org/W6762573206","https://openalex.org/W6774314701","https://openalex.org/W6784660784","https://openalex.org/W6794509127","https://openalex.org/W6801126751"],"related_works":["https://openalex.org/W2368605798","https://openalex.org/W2518037665","https://openalex.org/W2348524959","https://openalex.org/W2477036161","https://openalex.org/W2368049389","https://openalex.org/W2384861574","https://openalex.org/W4294565801","https://openalex.org/W2170801710","https://openalex.org/W2952704802","https://openalex.org/W4390723067"],"abstract_inverted_index":{"Unsupervised":[0],"region":[1,63,87,103,125,153,164],"representation":[2,54,64,95],"learning":[3,52,65,118,131],"aims":[4],"to":[5,58,122,139],"extract":[6],"dense":[7],"and":[8,66,97,127,144,163,182],"effective":[9,94],"features":[10],"from":[11,43],"unlabeled":[12],"urban":[13],"data.":[14],"While":[15],"some":[16],"efforts":[17],"have":[18],"been":[19],"made":[20],"for":[21,53,61,93,109],"solving":[22],"this":[23],"problem":[24],"based":[25],"on":[26],"multiple":[27],"views,":[28],"existing":[29],"methods":[30],"are":[31,185],"still":[32],"insufficient":[33],"in":[34,37,155,188],"extracting":[35],"representations":[36,42],"a":[38,68,86,102,136],"view":[39,92],"and/or":[40],"incorporating":[41],"different":[44,107],"views.":[45],"Motivated":[46],"by":[47,78],"the":[48,115,128,141,151,183,189],"success":[49],"of":[50],"contrastive":[51,117,130],"learning,":[55],"we":[56],"propose":[57],"leverage":[59],"it":[60],"multi-view":[62],"design":[67,114],"model":[69,172],"called":[70],"ReMVC":[71],"(Region":[72],"Embedding":[73],"with":[74,88,104,177],"Multi-View":[75],"Contrastive":[76],"Learning)":[77],"following":[79],"two":[80,156],"guidelines:":[81],"<inline-formula><tex-math":[82,98],"notation=\"LaTeX\">$i$</tex-math></inline-formula>":[83],")":[84,100],"comparing":[85,101],"others":[89],"within":[90],"each":[91],"extraction":[96],"notation=\"LaTeX\">$ii$</tex-math></inline-formula>":[99],"itself":[105],"across":[106,147],"views":[108],"cross-view":[110],"information":[111],"sharing.":[112],"We":[113,149],"intra-view":[116],"module":[119,132],"which":[120,133],"helps":[121],"learn":[123],"distinguished":[124],"embeddings":[126,154],"inter-view":[129],"serves":[134],"as":[135],"soft":[137],"co-regularizer":[138],"constrain":[140],"embedding":[142],"parameters":[143],"transfer":[145],"knowledge":[146],"multi-views.":[148],"exploit":[150],"learned":[152],"downstream":[157],"tasks":[158],"named":[159],"land":[160,190],"usage":[161,191],"clustering":[162,192],"popularity":[165],"prediction.":[166],"Extensive":[167],"experiments":[168],"demonstrate":[169],"that":[170],"our":[171],"achieves":[173],"impressive":[174],"improvements":[175],"compared":[176],"seven":[178],"state-of-the-art":[179],"baseline":[180],"methods,":[181],"margins":[184],"over":[186],"30%":[187],"task.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-11T08:14:18.477133","created_date":"2025-10-10T00:00:00"}