{"id":"https://openalex.org/W4385701310","doi":"https://doi.org/10.1007/978-3-031-39831-5_12","title":"DBGAN: A Data Balancing Generative Adversarial Network for\u00a0Mobility Pattern Recognition","display_name":"DBGAN: A Data Balancing Generative Adversarial Network for\u00a0Mobility Pattern Recognition","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4385701310","doi":"https://doi.org/10.1007/978-3-031-39831-5_12"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-031-39831-5_12","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-39831-5_12","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1007/978-3-031-39831-5_12","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081497281","display_name":"Ke Zhang","orcid":"https://orcid.org/0000-0003-2714-5587"},"institutions":[{"id":"https://openalex.org/I205274468","display_name":"Trinity College Dublin","ror":"https://ror.org/02tyrky19","country_code":"IE","type":"education","lineage":["https://openalex.org/I205274468"]}],"countries":["IE"],"is_corresponding":true,"raw_author_name":"Ke Zhang","raw_affiliation_strings":["Trinity College Dublin, Dublin, D02 R123, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Trinity College Dublin, Dublin, D02 R123, Ireland","institution_ids":["https://openalex.org/I205274468"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076290816","display_name":"Hengchang Liu","orcid":"https://orcid.org/0000-0002-9006-0546"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengchang Liu","raw_affiliation_strings":["The University of Electronic Science and Technology of China, Chengdu, Sichuan, 611731, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Electronic Science and Technology of China, Chengdu, Sichuan, 611731, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047083691","display_name":"Siobh\u00e1n Clarke","orcid":"https://orcid.org/0000-0001-5721-9976"},"institutions":[{"id":"https://openalex.org/I205274468","display_name":"Trinity College Dublin","ror":"https://ror.org/02tyrky19","country_code":"IE","type":"education","lineage":["https://openalex.org/I205274468"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Siobh\u00e1n Clarke","raw_affiliation_strings":["Trinity College Dublin, Dublin, D02 R123, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Trinity College Dublin, Dublin, D02 R123, Ireland","institution_ids":["https://openalex.org/I205274468"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5081497281"],"corresponding_institution_ids":["https://openalex.org/I205274468"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":{"value":5000,"currency":"EUR","value_usd":5392},"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"120","last_page":"134"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9976000189781189,"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":0.9976000189781189,"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":0.9951000213623047,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8922510147094727},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.72080397605896},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6206849217414856},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.5972270965576172},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.504571795463562},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4032030701637268},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.137681245803833}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8922510147094727},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.72080397605896},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6206849217414856},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.5972270965576172},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.504571795463562},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4032030701637268},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.137681245803833}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-031-39831-5_12","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-39831-5_12","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.1007/978-3-031-39831-5_12","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-39831-5_12","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2077933344","https://openalex.org/W2104167780","https://openalex.org/W2148143831","https://openalex.org/W2174519730","https://openalex.org/W2768444160","https://openalex.org/W2784189535","https://openalex.org/W2801840486","https://openalex.org/W2904970799","https://openalex.org/W2969106118","https://openalex.org/W2996303435","https://openalex.org/W3005040888","https://openalex.org/W3083480032","https://openalex.org/W3092567586","https://openalex.org/W3113533892","https://openalex.org/W3120727163","https://openalex.org/W3133149680","https://openalex.org/W3151130473","https://openalex.org/W3207792616","https://openalex.org/W3210047443","https://openalex.org/W3213422146","https://openalex.org/W4221050045","https://openalex.org/W4223422807","https://openalex.org/W4223499953","https://openalex.org/W4223918756","https://openalex.org/W4226139500","https://openalex.org/W4296767570","https://openalex.org/W4309332691"],"related_works":["https://openalex.org/W2033914206","https://openalex.org/W2042327336","https://openalex.org/W2888032422","https://openalex.org/W2996316059","https://openalex.org/W4385421777","https://openalex.org/W4377980832","https://openalex.org/W2897769091","https://openalex.org/W2845413374","https://openalex.org/W3005996785","https://openalex.org/W4297411772"],"abstract_inverted_index":{"Mobility":[0],"pattern":[1,85,135,208],"recognition":[2],"is":[3,71,123,172],"a":[4,40,62,72,117],"central":[5],"aspect":[6],"of":[7,16,100,166,200],"transportation":[8,145,218],"and":[9,94,104,132,152,162,210,219],"data":[10,49,129,148,204,220],"mining":[11,221],"research.":[12],"Despite":[13],"the":[14,128,139,177,182,185,192,198],"development":[15],"various":[17],"machine":[18],"learning":[19],"techniques":[20],"for":[21,214],"this":[22,58],"problem,":[23],"most":[24],"existing":[25],"methods":[26],"face":[27],"challenges":[28,82],"such":[29,42],"as":[30,43],"reliance":[31],"on":[32,116,142,154],"handcrafted":[33,107],"features":[34,99,108],"(e.g.,":[35,51,91,96],"user":[36],"has":[37],"to":[38,79,126,174],"specify":[39],"feature":[41],"\u201ctravel":[44],"time\u201d)":[45],"or":[46],"issues":[47],"with":[48,184,191],"imbalance":[50,130,205],"fewer":[52],"older":[53,160],"travelers":[54],"than":[55],"commuters).":[56],"In":[57],"paper,":[59],"we":[60],"introduce":[61],"novel":[63],"Data":[64],"Balancing":[65],"Generative":[66],"Adversarial":[67],"Network":[68],"(DBGAN),":[69],"which":[70],"specifically":[73],"designed":[74],"attention":[75],"mechanism-based":[76],"GAN":[77],"model":[78,122],"address":[80],"these":[81],"in":[83,112,181,202,206,217],"mobility":[84,134,187,207],"recognition.":[86,136],"DBGAN":[87,171,201],"captures":[88],"both":[89],"static":[90],"travel":[92,97],"locations)":[93],"dynamic":[95],"times)":[98],"different":[101,157,178],"passenger":[102,158,179],"groups,":[103],"avoids":[105],"using":[106],"that":[109,170],"may":[110],"result":[111],"information":[113],"loss,":[114],"based":[115],"sequence-to-image":[118],"embedding":[119],"method.":[120],"Our":[121],"then":[124],"applied":[125],"overcome":[127],"issue":[131],"perform":[133],"We":[137],"evaluate":[138],"proposed":[140],"method":[141],"real-world":[143],"public":[144],"smart":[146],"card":[147],"from":[149],"Suzhou,":[150],"China,":[151],"focus":[153],"recognizing":[155],"two":[156],"groups:":[159],"people":[161],"students.":[163],"The":[164],"results":[165,196],"our":[167],"experiments":[168],"demonstrate":[169,211],"able":[173],"accurately":[175],"identify":[176],"groups":[180],"data,":[183],"detected":[186],"patterns":[188],"being":[189],"consistent":[190],"ground":[193],"truth.":[194],"These":[195],"highlight":[197],"effectiveness":[199],"overcoming":[203],"recognition,":[209],"its":[212],"potential":[213],"wider":[215],"use":[216],"applications.":[222]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
