{"id":"https://openalex.org/W4406461529","doi":"https://doi.org/10.1109/bigdata62323.2024.10825688","title":"DUGET: Leveraging Machine Learning for Dynamic User Grouping and Evolution Tracking in Public Transit Systems","display_name":"DUGET: Leveraging Machine Learning for Dynamic User Grouping and Evolution Tracking in Public Transit Systems","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406461529","doi":"https://doi.org/10.1109/bigdata62323.2024.10825688"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825688","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825688","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-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/A5115905162","display_name":"Tobias Johannesson","orcid":null},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Tobias Johannesson","raw_affiliation_strings":["KTH Royal Institute of Technology,Department of Computer Science,Stockholm,Sweden"],"affiliations":[{"raw_affiliation_string":"KTH Royal Institute of Technology,Department of Computer Science,Stockholm,Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019124129","display_name":"Isak Rubensson","orcid":"https://orcid.org/0000-0003-0307-7946"},"institutions":[{"id":"https://openalex.org/I146360087","display_name":"Swedish Transport Administration","ror":"https://ror.org/000nes056","country_code":"SE","type":"government","lineage":["https://openalex.org/I146360087"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Isak Rubensson","raw_affiliation_strings":["Transport Administration Region,Stockholm,Sweden"],"affiliations":[{"raw_affiliation_string":"Transport Administration Region,Stockholm,Sweden","institution_ids":["https://openalex.org/I146360087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023575593","display_name":"Sina Sheikholeslami","orcid":"https://orcid.org/0000-0001-7236-4637"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Sina Sheikholeslami","raw_affiliation_strings":["KTH Royal Institute of Technology,Department of Computer Science,Stockholm,Sweden"],"affiliations":[{"raw_affiliation_string":"KTH Royal Institute of Technology,Department of Computer Science,Stockholm,Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080481315","display_name":"Ahmad Al-Shishtawy","orcid":"https://orcid.org/0000-0002-9546-4937"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Ahmad Al-Shishtawy","raw_affiliation_strings":["KTH Royal Institute of Technology,Department of Computer Science,Stockholm,Sweden"],"affiliations":[{"raw_affiliation_string":"KTH Royal Institute of Technology,Department of Computer Science,Stockholm,Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042422836","display_name":"Vladimir Vlassov","orcid":"https://orcid.org/0000-0002-6779-7435"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Vladimir Vlassov","raw_affiliation_strings":["KTH Royal Institute of Technology,Department of Computer Science,Stockholm,Sweden"],"affiliations":[{"raw_affiliation_string":"KTH Royal Institute of Technology,Department of Computer Science,Stockholm,Sweden","institution_ids":["https://openalex.org/I86987016"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5115905162"],"corresponding_institution_ids":["https://openalex.org/I86987016"],"apc_list":null,"apc_paid":null,"fwci":0.6727,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.79558749,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1785","last_page":"1794"},"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9993000030517578,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9977999925613403,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7743303775787354},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.6103591322898865},{"id":"https://openalex.org/keywords/public-transport","display_name":"Public transport","score":0.5997909903526306},{"id":"https://openalex.org/keywords/transit","display_name":"Transit (satellite)","score":0.5554128289222717},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4501691162586212},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3372875452041626},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12081298232078552},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.07889512181282043}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7743303775787354},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.6103591322898865},{"id":"https://openalex.org/C539828613","wikidata":"https://www.wikidata.org/wiki/Q178512","display_name":"Public transport","level":2,"score":0.5997909903526306},{"id":"https://openalex.org/C2778022998","wikidata":"https://www.wikidata.org/wiki/Q651136","display_name":"Transit (satellite)","level":3,"score":0.5554128289222717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4501691162586212},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3372875452041626},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12081298232078552},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.07889512181282043},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825688","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825688","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2432060681","https://openalex.org/W2795245935","https://openalex.org/W2803241079","https://openalex.org/W2944507549","https://openalex.org/W2946687390","https://openalex.org/W3007606974","https://openalex.org/W3162915151","https://openalex.org/W3176933695","https://openalex.org/W4281660018","https://openalex.org/W4406461529","https://openalex.org/W6736123895","https://openalex.org/W6739498180","https://openalex.org/W6753849576","https://openalex.org/W6780797579","https://openalex.org/W6789598141","https://openalex.org/W6805178389","https://openalex.org/W6809889162"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3048859969","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W2052743154"],"abstract_inverted_index":{"This":[0],"work":[1],"aims":[2],"to":[3,17,199],"explore":[4],"the":[5,149,168],"use":[6],"of":[7,89,153,170,204],"machine":[8],"learning":[9],"techniques,":[10],"particularly":[11],"clustering":[12],"and":[13,27,35,40,51,73,82,114,126,151,192],"cluster":[14,83],"evolution":[15,84],"tracking,":[16],"analyze":[18],"travel":[19,128],"patterns":[20,129],"in":[21,24,57,79,164,175,202],"public":[22,160,176],"transportation":[23,161,177],"a":[25,107,131,158,183],"city":[26],"provide":[28,70],"valuable":[29,74],"insights":[30,75],"for":[31,148,196],"urban":[32],"transit":[33],"planning":[34],"optimization.":[36],"Clustering":[37,81],"involves":[38],"identifying":[39],"grouping":[41],"similar":[42],"objects,":[43],"such":[44,99],"as":[45,100,182],"passengers":[46,90],"with":[47],"different":[48],"ticket":[49,124],"types,":[50],"distinguishing":[52],"them":[53],"from":[54],"dissimilar":[55],"objects":[56],"other":[58],"groups.":[59],"Over":[60],"time,":[61],"groups":[62,88,203],"can":[63,69,86,193],"change,":[64],"so":[65],"tracking":[66,85,171],"this":[67],"change":[68,172],"more":[71,93],"detailed":[72],"than":[76],"analyzing":[77],"data":[78],"aggregates.":[80],"reveal":[87],"that":[91],"are":[92,136],"or":[94,102],"less":[95],"affected":[96],"by":[97,178],"changes":[98],"seasonality":[101],"fare":[103],"increases.":[104],"We":[105],"propose":[106,189],"framework":[108,187],"called":[109],"DUGET":[110],"(Dynamic":[111],"User":[112],"Grouping":[113],"Evolution":[115],"Tracking),":[116],"which":[117],"clusters":[118,135],"anonymized":[119],"users":[120],"based":[121,144],"on":[122,145],"their":[123],"choices":[125],"temporal":[127,184],"using":[130,141,157],"multi-step":[132],"approach.":[133],"The":[134,186],"then":[137],"tracked":[138],"over":[139,173],"time":[140,174],"Jaccard":[142],"similarity":[143],"memberships,":[146],"allowing":[147],"analysis":[150],"visualization":[152],"changes.":[154],"Our":[155],"experiments":[156],"real-world":[159],"dataset":[162],"collected":[163],"Stockholm,":[165],"Sweden,":[166],"show":[167],"feasibility":[169],"examining":[179],"passenger":[180],"behavior":[181],"aggregate.":[185],"we":[188],"is":[190],"generalizable":[191],"be":[194],"used":[195],"future":[197],"projects":[198],"understand":[200],"trends":[201],"objects.":[205]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}