{"id":"https://openalex.org/W4367046979","doi":"https://doi.org/10.1145/3543507.3583876","title":"Knowledge-infused Contrastive Learning for Urban Imagery-based Socioeconomic Prediction","display_name":"Knowledge-infused Contrastive Learning for Urban Imagery-based Socioeconomic Prediction","publication_year":2023,"publication_date":"2023-04-26","ids":{"openalex":"https://openalex.org/W4367046979","doi":"https://doi.org/10.1145/3543507.3583876"},"language":"en","primary_location":{"id":"doi:10.1145/3543507.3583876","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3543507.3583876","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3543507.3583876","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2023","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3543507.3583876","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004545610","display_name":"Yu Liu","orcid":"https://orcid.org/0000-0002-2399-2829"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yu Liu","raw_affiliation_strings":["Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042093698","display_name":"Xin Zhang","orcid":"https://orcid.org/0000-0002-2506-7370"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Zhang","raw_affiliation_strings":["Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052892856","display_name":"Jingtao Ding","orcid":"https://orcid.org/0000-0001-7985-6263"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingtao Ding","raw_affiliation_strings":["Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067943001","display_name":"Yanxin Xi","orcid":"https://orcid.org/0000-0003-4715-2186"},"institutions":[{"id":"https://openalex.org/I133731052","display_name":"University of Helsinki","ror":"https://ror.org/040af2s02","country_code":"FI","type":"education","lineage":["https://openalex.org/I133731052"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Yanxin Xi","raw_affiliation_strings":["University of Helsinki, Finland"],"affiliations":[{"raw_affiliation_string":"University of Helsinki, Finland","institution_ids":["https://openalex.org/I133731052"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100355277","display_name":"Yong Li","orcid":"https://orcid.org/0000-0001-5617-1659"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Li","raw_affiliation_strings":["Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5004545610"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":3.7013,"has_fulltext":true,"cited_by_count":31,"citation_normalized_percentile":{"value":0.94672687,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"4150","last_page":"4160"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9973000288009644,"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"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9973000288009644,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9973000288009644,"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/T11963","display_name":"Impact of Light on Environment and Health","score":0.9958999752998352,"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":0.7378401756286621},{"id":"https://openalex.org/keywords/socioeconomic-status","display_name":"Socioeconomic status","score":0.650227427482605},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5857346653938293},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.52004075050354},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4510112702846527},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.42732110619544983}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7378401756286621},{"id":"https://openalex.org/C147077947","wikidata":"https://www.wikidata.org/wiki/Q1515895","display_name":"Socioeconomic status","level":3,"score":0.650227427482605},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5857346653938293},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.52004075050354},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4510112702846527},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.42732110619544983},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3543507.3583876","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3543507.3583876","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3543507.3583876","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2023","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3543507.3583876","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3543507.3583876","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3543507.3583876","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2023","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7400000095367432,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1614471940","display_name":null,"funder_award_id":"2020AAA0","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3710896277","display_name":null,"funder_award_id":"61971267","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3734416573","display_name":null,"funder_award_id":"61972223","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4872662616","display_name":null,"funder_award_id":"U1936217","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7024251178","display_name":null,"funder_award_id":"2020AAA0106000","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4367046979.pdf","grobid_xml":"https://content.openalex.org/works/W4367046979.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1979728958","https://openalex.org/W2058336014","https://openalex.org/W2106698616","https://openalex.org/W2112738128","https://openalex.org/W2513506629","https://openalex.org/W2618530766","https://openalex.org/W2737258237","https://openalex.org/W2741267865","https://openalex.org/W2759136286","https://openalex.org/W2770820547","https://openalex.org/W2798754085","https://openalex.org/W2799003896","https://openalex.org/W2914592219","https://openalex.org/W2939078500","https://openalex.org/W2964246847","https://openalex.org/W2998302682","https://openalex.org/W3010336026","https://openalex.org/W3023371261","https://openalex.org/W3027716283","https://openalex.org/W3033427317","https://openalex.org/W3034277777","https://openalex.org/W3042772844","https://openalex.org/W3080604000","https://openalex.org/W3081189998","https://openalex.org/W3096934659","https://openalex.org/W3097348804","https://openalex.org/W3103296573","https://openalex.org/W3118428491","https://openalex.org/W3133683052","https://openalex.org/W3173151551","https://openalex.org/W3174507861","https://openalex.org/W3183523595","https://openalex.org/W3185276638","https://openalex.org/W3211468413","https://openalex.org/W4224317403","https://openalex.org/W4229004105","https://openalex.org/W4288101107","https://openalex.org/W4307330169"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Monitoring":[0],"sustainable":[1],"development":[2],"goals":[3],"requires":[4],"accurate":[5],"and":[6,12,49,58,98,115,141,186,192],"timely":[7],"socioeconomic":[8,29,51,79,156,201],"statistics,":[9],"while":[10],"ubiquitous":[11],"frequently-updated":[13],"urban":[14,45,77,92,110,199],"imagery":[15,46,188],"in":[16,65,94,112],"web":[17],"like":[18],"satellite/street":[19],"view":[20],"images":[21],"has":[22],"emerged":[23],"as":[24],"an":[25,109],"important":[26],"source":[27],"for":[28,44,76,144,155],"prediction.":[30,80,202],"Especially,":[31,176],"recent":[32],"studies":[33],"turn":[34],"to":[35,88,105,183],"self-supervised":[36],"contrastive":[37,125,132],"learning":[38,48,126],"with":[39,128,167,174,189],"manually":[40],"designed":[41],"similarity":[42],"metrics":[43],"representation":[47],"further":[50],"prediction,":[52],"which":[53,134,195],"however":[54],"suffers":[55],"from":[56],"effectiveness":[57,191],"robustness":[59],"issues.":[60],"To":[61],"address":[62],"such":[63],"issues,":[64],"this":[66],"paper,":[67],"we":[68,82,120],"propose":[69],"a":[70,122,129],"Knowledge-infused":[71],"Contrastive":[72],"Learning":[73],"(KnowCL)":[74],"model":[75,90,180],"imagery-based":[78,200],"Specifically,":[81],"firstly":[83],"introduce":[84],"knowledge":[85,93,145],"graph":[86],"(KG)":[87],"effectively":[89],"the":[91,136,151,162],"spatiality,":[95],"mobility,":[96],"etc.,":[97],"then":[99],"build":[100],"neural":[101],"network":[102],"based":[103,124],"encoders":[104],"learn":[106],"representations":[107,143,154],"of":[108,149,165],"image":[111],"associated":[113],"semantic":[114,140],"visual":[116,142,153],"spaces,":[117],"respectively.":[118],"Finally,":[119],"design":[121],"cross-modality":[123],"framework":[127],"novel":[130],"image-KG":[131],"loss,":[133],"maximizes":[135],"mutual":[137],"information":[138],"between":[139],"infusion.":[146],"Extensive":[147],"experiments":[148],"applying":[150],"learnt":[152],"prediction":[157],"on":[158,171],"three":[159],"datasets":[160],"demonstrate":[161],"superior":[163],"performance":[164],"KnowCL":[166,179],"over":[168],"30%":[169],"improvements":[170],"R2":[172],"compared":[173],"baselines.":[175],"our":[177],"proposed":[178],"can":[181],"apply":[182],"both":[184,190],"satellite":[185],"street":[187],"transferability":[193],"achieved,":[194],"provides":[196],"insights":[197],"into":[198]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":7}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}