{"id":"https://openalex.org/W4388834517","doi":"https://doi.org/10.1145/3615886.3627749","title":"Tensor Dirichlet Process Multinomial Mixture Model with Graphs for Passenger Trajectory Clustering","display_name":"Tensor Dirichlet Process Multinomial Mixture Model with Graphs for Passenger Trajectory Clustering","publication_year":2023,"publication_date":"2023-11-13","ids":{"openalex":"https://openalex.org/W4388834517","doi":"https://doi.org/10.1145/3615886.3627749"},"language":"en","primary_location":{"id":"doi:10.1145/3615886.3627749","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3615886.3627749","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery","raw_type":"proceedings-article"},"type":"conference-paper","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/A5029997962","display_name":"Ziyue Li","orcid":"https://orcid.org/0000-0003-4983-9352"},"institutions":[{"id":"https://openalex.org/I180923762","display_name":"University of Cologne","ror":"https://ror.org/00rcxh774","country_code":"DE","type":"education","lineage":["https://openalex.org/I180923762"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ziyue Li","raw_affiliation_strings":["University of Cologne, Cologne, NRW, Germany"],"raw_orcid":"https://orcid.org/0000-0003-4983-9352","affiliations":[{"raw_affiliation_string":"University of Cologne, Cologne, NRW, Germany","institution_ids":["https://openalex.org/I180923762"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100652901","display_name":"Hao Yan","orcid":"https://orcid.org/0000-0002-4322-7323"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hao Yan","raw_affiliation_strings":["Arizona State University, Tempe, U.S.A"],"raw_orcid":"https://orcid.org/0000-0002-4322-7323","affiliations":[{"raw_affiliation_string":"Arizona State University, Tempe, U.S.A","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100374122","display_name":"Chen Zhang","orcid":"https://orcid.org/0000-0002-4767-9597"},"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":"Chen Zhang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4767-9597","affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042852488","display_name":"Wolfgang Ketter","orcid":"https://orcid.org/0000-0001-9008-142X"},"institutions":[{"id":"https://openalex.org/I180923762","display_name":"University of Cologne","ror":"https://ror.org/00rcxh774","country_code":"DE","type":"education","lineage":["https://openalex.org/I180923762"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Wolfgang Ketter","raw_affiliation_strings":["University of Cologne, Cologne, NRW, Germany"],"raw_orcid":"https://orcid.org/0000-0001-9008-142X","affiliations":[{"raw_affiliation_string":"University of Cologne, Cologne, NRW, Germany","institution_ids":["https://openalex.org/I180923762"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048627515","display_name":"Fugee Tsung","orcid":"https://orcid.org/0000-0002-0575-8254"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Fugee Tsung","raw_affiliation_strings":["The Hong Kong University of Science and Technology Kowloon, Hong Kong SAR, HKUST-GZ, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-0575-8254","affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology Kowloon, Hong Kong SAR, HKUST-GZ, Guangzhou, China","institution_ids":["https://openalex.org/I200769079","https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"121","last_page":"128"},"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":0.9933000206947327,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9883000254631042,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer 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":0.7122141718864441},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7001180648803711},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5414227843284607},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5216893553733826},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4947030246257782},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.4664928913116455},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.43351489305496216},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.42584189772605896},{"id":"https://openalex.org/keywords/hierarchical-clustering","display_name":"Hierarchical clustering","score":0.422515332698822},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1930147111415863},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1895914077758789}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7122141718864441},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7001180648803711},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5414227843284607},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5216893553733826},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4947030246257782},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.4664928913116455},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.43351489305496216},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.42584189772605896},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.422515332698822},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1930147111415863},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1895914077758789},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1145/3615886.3627749","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3615886.3627749","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.eur.nl:publications/2b75e166-db6e-4996-8c84-a5516605c8b0","is_oa":false,"landing_page_url":"https://pure.eur.nl/en/publications/2b75e166-db6e-4996-8c84-a5516605c8b0","pdf_url":null,"source":{"id":"https://openalex.org/S4306401266","display_name":"EUR Research Repository (Erasmus University Rotterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I913958620","host_organization_name":"Erasmus University Rotterdam","host_organization_lineage":["https://openalex.org/I913958620"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Li, Z, Yan, H, Zhang, C, Ketter, W & Tsung, F 2023, Tensor Dirichlet Process Multinomial Mixture Model with Graphs for Passenger Trajectory Clustering. in S Newsam, L Yang, G Mai, B Martins, D Lunga & S Gao (eds), GeoAI 2023 - Proceedings of the 6th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery. Association for Computing Machinery (ACM), GeoAI 2023 - Proceedings of the 6th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, pp. 121-128, 6th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2023, Hamburg, Germany, 13/11/23. https://doi.org/10.1145/3615886.3627749","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:USBKOELN.ub.uni-koeln.de:73007","is_oa":false,"landing_page_url":"https://orcid.org/0000-0003-4983-9352>,","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Book Section"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-136499","is_oa":false,"landing_page_url":"https://repository.hkust.edu.hk/ir/Record/1783.1-136499","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"},{"id":"pmh:oai:USBKOELN.ub.uni-koeln.de:73007","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306400371","display_name":"K\u00f6lner Universit\u00e4ts PublikationsServer (Universit\u00e4t zu K\u00f6ln)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210115942","host_organization_name":"Rhenish Institute for Environmental Research","host_organization_lineage":["https://openalex.org/I4210115942"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"doc-type:bookPart"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1977556410","https://openalex.org/W2001082470","https://openalex.org/W2061922307","https://openalex.org/W2113586398","https://openalex.org/W2115870554","https://openalex.org/W2146341620","https://openalex.org/W2150461699","https://openalex.org/W2187089797","https://openalex.org/W2295258851","https://openalex.org/W2442340835","https://openalex.org/W2513361716","https://openalex.org/W2530551364","https://openalex.org/W2604537950","https://openalex.org/W2605048719","https://openalex.org/W2805066180","https://openalex.org/W2904832339","https://openalex.org/W2945591580","https://openalex.org/W2952293382","https://openalex.org/W2997311100","https://openalex.org/W3013929738","https://openalex.org/W3025226748","https://openalex.org/W3037245145","https://openalex.org/W4295990491"],"related_works":["https://openalex.org/W4323768008","https://openalex.org/W1941703695","https://openalex.org/W4248382324","https://openalex.org/W3131574667","https://openalex.org/W4360995134","https://openalex.org/W3023605104","https://openalex.org/W2039473718","https://openalex.org/W2387529410","https://openalex.org/W2383578611","https://openalex.org/W3200375535"],"abstract_inverted_index":{"Passenger":[0],"clustering":[1,51],"based":[2,151],"on":[3,45,152],"trajectory":[4],"records":[5],"is":[6,158,182],"essential":[7],"for":[8],"transportation":[9],"operators.":[10],"However,":[11],"existing":[12,42,56],"methods":[13,57],"cannot":[14],"easily":[15],"cluster":[16,101,145,166,171],"the":[17,21,25,50,72,92,96,109,113,128,162],"passengers":[18],"due":[19],"to":[20,53,111,126,160],"hierarchical":[22,93],"structure":[23,94],"of":[24,49,95,115,137,165],"passenger":[26,34,156],"trip":[27,98],"information,":[28],"including":[29],"multiple":[30],"trips":[31],"within":[32],"each":[33,39],"and":[35,68,100,169,177],"multi-dimensional":[36,97],"information":[37,99],"about":[38],"trip.":[40],"Furthermore,":[41],"approaches":[43],"rely":[44],"an":[46],"accurate":[47],"specification":[48],"number":[52,114],"start.":[54],"Finally,":[55],"do":[58],"not":[59],"consider":[60],"spatial":[61,119],"semantic":[62,129],"graphs":[63,120],"such":[64],"as":[65],"geographical":[66],"proximity":[67],"functional":[69],"similarity":[70],"between":[71],"locations.":[73],"In":[74],"this":[75],"paper,":[76],"we":[77],"propose":[78,133],"a":[79,104,134,143],"novel":[80],"tensor":[81,135],"Dirichlet":[82],"Process":[83],"Multinomial":[84],"Mixture":[85],"model":[86],"with":[87,108,142],"graphs,":[88],"which":[89],"can":[90],"preserve":[91],"them":[102],"in":[103,123],"unified":[105],"one-step":[106],"manner":[107],"ability":[110],"determine":[112],"clusters":[116],"automatically.":[117],"The":[118,180],"are":[121],"utilized":[122],"community":[124],"detection":[125],"link":[127],"neighbors.":[130],"We":[131],"further":[132],"version":[136],"Collapsed":[138],"Gibbs":[139],"Sampling":[140],"method":[141],"minimum":[144],"size":[146],"requirement.":[147],"A":[148],"case":[149],"study":[150],"Hong":[153],"Kong":[154],"metro":[155],"data":[157],"conducted":[159],"demonstrate":[161],"automatic":[163],"process":[164],"amount":[167],"evolution":[168],"better":[170],"quality":[172],"measured":[173],"by":[174],"within-cluster":[175],"compactness":[176],"cross-cluster":[178],"separateness.":[179],"code":[181],"available":[183],"at":[184],"https://github.com/bonaldli/TensorDPMM-G.":[185]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
