{"id":"https://openalex.org/W4205209477","doi":"https://doi.org/10.1109/tnet.2021.3136707","title":"Deep Transfer Learning Across Cities for Mobile Traffic Prediction","display_name":"Deep Transfer Learning Across Cities for Mobile Traffic Prediction","publication_year":2021,"publication_date":"2021-12-23","ids":{"openalex":"https://openalex.org/W4205209477","doi":"https://doi.org/10.1109/tnet.2021.3136707"},"language":"en","primary_location":{"id":"doi:10.1109/tnet.2021.3136707","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnet.2021.3136707","pdf_url":null,"source":{"id":"https://openalex.org/S62238642","display_name":"IEEE/ACM Transactions on Networking","issn_l":"1063-6692","issn":["1063-6692","1558-2566"],"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/ACM Transactions on Networking","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/A5023787839","display_name":"Qiong Wu","orcid":"https://orcid.org/0000-0002-2156-4433"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiong Wu","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-2156-4433","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022823142","display_name":"Kaiwen He","orcid":"https://orcid.org/0000-0003-3665-6178"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaiwen He","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-3665-6178","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100385692","display_name":"Xu Chen","orcid":"https://orcid.org/0000-0001-9943-6020"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Chen","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9943-6020","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053629236","display_name":"Shuai Yu","orcid":"https://orcid.org/0000-0001-6822-3145"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Yu","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6822-3145","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027033026","display_name":"Junshan Zhang","orcid":"https://orcid.org/0000-0002-3840-1753"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junshan Zhang","raw_affiliation_strings":["ECE Department, University of California at Davis, Davis, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-3840-1753","affiliations":[{"raw_affiliation_string":"ECE Department, University of California at Davis, Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0184,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.91219078,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"30","issue":"3","first_page":"1255","last_page":"1267"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998999834060669,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9970999956130981,"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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9872999787330627,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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":0.8455395698547363},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6679112911224365},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.583397626876831},{"id":"https://openalex.org/keywords/provisioning","display_name":"Provisioning","score":0.5386194586753845},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43072906136512756},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.42207539081573486},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34378135204315186},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.27878132462501526},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.09874841570854187}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8455395698547363},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6679112911224365},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.583397626876831},{"id":"https://openalex.org/C172191483","wikidata":"https://www.wikidata.org/wiki/Q1071806","display_name":"Provisioning","level":2,"score":0.5386194586753845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43072906136512756},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.42207539081573486},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34378135204315186},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.27878132462501526},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.09874841570854187}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tnet.2021.3136707","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnet.2021.3136707","pdf_url":null,"source":{"id":"https://openalex.org/S62238642","display_name":"IEEE/ACM Transactions on Networking","issn_l":"1063-6692","issn":["1063-6692","1558-2566"],"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/ACM Transactions on Networking","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7799999713897705}],"awards":[{"id":"https://openalex.org/G3583843466","display_name":"\u9762\u5411\u79fb\u52a8\u5927\u6570\u636e\u5e94\u7528\u7684\u591a\u5c42\u6b21\u878d\u5408\u9ad8\u6548\u8fb9\u7f18\u8ba1\u7b97\u7814\u7a76","funder_award_id":"61972432","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5121664804","display_name":null,"funder_award_id":"U1711265","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G645405385","display_name":null,"funder_award_id":"U20A20159","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G969433377","display_name":null,"funder_award_id":"2017GC010465","funder_id":"https://openalex.org/F4320334009","funder_display_name":"Guangdong Provincial Pearl River Talents Program"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334009","display_name":"Guangdong Provincial Pearl River Talents Program","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1534304300","https://openalex.org/W1986620394","https://openalex.org/W1991898587","https://openalex.org/W2009139797","https://openalex.org/W2104068492","https://openalex.org/W2140405352","https://openalex.org/W2161901213","https://openalex.org/W2165698076","https://openalex.org/W2172064003","https://openalex.org/W2174519730","https://openalex.org/W2190432600","https://openalex.org/W2214409633","https://openalex.org/W2514159439","https://openalex.org/W2786808285","https://openalex.org/W2787753888","https://openalex.org/W2789386460","https://openalex.org/W2807536558","https://openalex.org/W2811507150","https://openalex.org/W2889260512","https://openalex.org/W2907637692","https://openalex.org/W2913340405","https://openalex.org/W2917443388","https://openalex.org/W2921319277","https://openalex.org/W2936185297","https://openalex.org/W2939911019","https://openalex.org/W2961380111","https://openalex.org/W2963035276","https://openalex.org/W2963049813","https://openalex.org/W2963165299","https://openalex.org/W2963709863","https://openalex.org/W2966783050","https://openalex.org/W2982355056","https://openalex.org/W3006842217","https://openalex.org/W3127284993","https://openalex.org/W3129005378","https://openalex.org/W4288086393","https://openalex.org/W6608710415","https://openalex.org/W6631190155","https://openalex.org/W6685352114","https://openalex.org/W6762042405"],"related_works":["https://openalex.org/W4206357785","https://openalex.org/W3192840557","https://openalex.org/W4281381188","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3023427754","https://openalex.org/W4375928479","https://openalex.org/W3131673289","https://openalex.org/W4380075502","https://openalex.org/W3049131298"],"abstract_inverted_index":{"Precise":[0],"citywide":[1,72,172],"mobile":[2,36,73,106,158,173],"traffic":[3,18,37,74,107,159,174],"prediction":[4,19,47,75,175],"is":[5],"of":[6,35,97,105,139],"great":[7],"significance":[8],"for":[9,28,40,71,121,150],"intelligent":[10],"network":[11,116],"planning":[12],"and":[13,90,127],"proactive":[14],"service":[15],"provisioning.":[16],"Current":[17],"approaches":[20],"mainly":[21],"focus":[22],"on":[23,156],"training":[24],"a":[25,32,62,85,98],"well-performed":[26],"model":[27,89,93],"the":[29,41,46,92],"cities":[30,42,77],"with":[31,43,78,132,176],"large":[33],"amount":[34],"data.":[38,129],"However,":[39],"scarce":[44],"data,":[45],"performance":[48,151,170],"will":[49],"be":[50],"greatly":[51],"limited.":[52],"To":[53,130],"tackle":[54],"this":[55,58],"problem,":[56],"in":[57,76,136,171],"paper":[59],"we":[60,82,142],"propose":[61],"novel":[63,86],"cross-city":[64],"deep":[65],"transfer":[66,147],"learning":[67,88,148],"framework":[68,166],"named":[69],"CCTP":[70,165],"data":[79,96,126,133,177],"scarcity.":[80,178],"Specifically,":[81],"first":[83],"present":[84],"spatial-temporal":[87],"pre-train":[91],"by":[94],"abundant":[95],"source":[99,128],"city":[100],"to":[101],"obtain":[102],"prior":[103],"knowledge":[104],"dynamics.":[108],"We":[109],"then":[110],"devise":[111],"an":[112,145],"efficient":[113],"generative":[114],"adversarial":[115],"(GAN)":[117],"based":[118],"cross-domain":[119],"adapter":[120],"distribution":[122],"alignment":[123],"between":[124],"target":[125,140],"deal":[131],"scarcity":[134],"issue":[135],"some":[137],"clusters":[138],"city,":[141],"further":[143],"design":[144],"inter-cluster":[146],"strategy":[149],"enhancement.":[152],"Extensive":[153],"experiments":[154],"conducted":[155],"real-world":[157],"datasets":[160],"demonstrate":[161],"that":[162],"our":[163],"proposed":[164],"can":[167],"achieve":[168],"superior":[169]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}