{"id":"https://openalex.org/W4306317480","doi":"https://doi.org/10.1145/3511808.3557308","title":"Efficient Trajectory Similarity Computation with Contrastive Learning","display_name":"Efficient Trajectory Similarity Computation with Contrastive Learning","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4306317480","doi":"https://doi.org/10.1145/3511808.3557308"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557308","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557308","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://dl.acm.org/doi/10.1145/3511808.3557308","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102981777","display_name":"Liwei Deng","orcid":"https://orcid.org/0000-0002-9377-4309"},"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":"Liwei Deng","raw_affiliation_strings":["University of Electronic Science and Technology of China, Cheng Du, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Cheng Du, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060365518","display_name":"Yan Zhao","orcid":"https://orcid.org/0000-0002-0242-3707"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Yan Zhao","raw_affiliation_strings":["Aalborg University, Aalborg, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aalborg University, Aalborg, Denmark","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073118844","display_name":"Zidan Fu","orcid":null},"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":"Zidan Fu","raw_affiliation_strings":["University of Electronic Science and Technology of China, Cheng Du, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Cheng Du, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037488877","display_name":"Hao Sun","orcid":"https://orcid.org/0000-0001-8456-7925"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Sun","raw_affiliation_strings":["Peking University, Peking, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, Peking, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066308099","display_name":"Shuncheng Liu","orcid":"https://orcid.org/0000-0003-3557-6598"},"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":"Shuncheng Liu","raw_affiliation_strings":["University of Electronic Science and Technology of China, Cheng Du, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Cheng Du, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100603979","display_name":"Kai Zheng","orcid":"https://orcid.org/0000-0002-0217-3998"},"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":"Kai Zheng","raw_affiliation_strings":["University of Electronic Science and Technology of China, Cheng Du, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Cheng Du, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.8249,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.97908065,"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":"365","last_page":"374"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/trajectory","display_name":"Trajectory","score":0.7321304678916931},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7311084270477295},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6973448991775513},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6175768375396729},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5682492256164551},{"id":"https://openalex.org/keywords/contrastive-analysis","display_name":"Contrastive analysis","score":0.43355846405029297},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.39548343420028687},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34993159770965576},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22471454739570618},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.1507180631160736},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09573960304260254}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7321304678916931},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7311084270477295},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6973448991775513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6175768375396729},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5682492256164551},{"id":"https://openalex.org/C2777629044","wikidata":"https://www.wikidata.org/wiki/Q614959","display_name":"Contrastive analysis","level":2,"score":0.43355846405029297},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.39548343420028687},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34993159770965576},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22471454739570618},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1507180631160736},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09573960304260254},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3511808.3557308","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557308","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:openaire/a2f83b3c-a251-4982-bea0-b41e4602bea0","is_oa":true,"landing_page_url":"https://dl.acm.org/doi/10.1145/3511808.3557308","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Deng, L, Zhao, Y, Fu, Z, Sun, H, Liu, S & Zheng, K 2022, Efficient Trajectory Similarity Computation with Contrastive Learning. in CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management. Association for Computing Machinery (ACM), pp. 365\u2013374, 31st ACM International Conference on Information and Knowledge Management, Atlanta, United States, 17/10/2022. https://doi.org/10.1145/3511808.3557308","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:pure.atira.dk:publications/0364f7a3-0435-44d7-a710-ab30ec4827e4","is_oa":false,"landing_page_url":"https://vbn.aau.dk/da/publications/0364f7a3-0435-44d7-a710-ab30ec4827e4","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Deng, L, Zhao, Y, Fu, Z, Sun, H, Liu, S & Zheng, K 2022, Efficient Trajectory Similarity Computation with Contrastive Learning. in CIKM. pp. 365-374. https://doi.org/10.1145/3511808.3557308","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:pure.atira.dk:publications/a2f83b3c-a251-4982-bea0-b41e4602bea0","is_oa":false,"landing_page_url":"https://vbn.aau.dk/da/publications/a2f83b3c-a251-4982-bea0-b41e4602bea0","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Deng , L , Zhao , Y , Fu , Z , Sun , H , Liu , S &amp; Zheng , K 2022 , Efficient Trajectory Similarity Computation with Contrastive Learning . in CIKM '22: Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management . Association for Computing Machinery , pp. 365\u2013374 , 31st ACM International Conference on Information and Knowledge Management , Atlanta , United States , 17/10/2022 . https://doi.org/10.1145/3511808.3557308","raw_type":"contributionToPeriodical"}],"best_oa_location":{"id":"pmh:oai:pure.atira.dk:openaire/a2f83b3c-a251-4982-bea0-b41e4602bea0","is_oa":true,"landing_page_url":"https://dl.acm.org/doi/10.1145/3511808.3557308","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Deng, L, Zhao, Y, Fu, Z, Sun, H, Liu, S & Zheng, K 2022, Efficient Trajectory Similarity Computation with Contrastive Learning. in CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management. Association for Computing Machinery (ACM), pp. 365\u2013374, 31st ACM International Conference on Information and Knowledge Management, Atlanta, United States, 17/10/2022. https://doi.org/10.1145/3511808.3557308","raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4099999964237213,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1531910981","https://openalex.org/W1567097384","https://openalex.org/W1864972570","https://openalex.org/W2015612071","https://openalex.org/W2049626361","https://openalex.org/W2064675550","https://openalex.org/W2072237376","https://openalex.org/W2118371392","https://openalex.org/W2124299914","https://openalex.org/W2136975357","https://openalex.org/W2337457909","https://openalex.org/W2622005089","https://openalex.org/W2943420531","https://openalex.org/W2952493731","https://openalex.org/W2970849355","https://openalex.org/W2987583674","https://openalex.org/W3009448889","https://openalex.org/W3013563398","https://openalex.org/W3034526875","https://openalex.org/W3035098013","https://openalex.org/W3082160640","https://openalex.org/W3169933468","https://openalex.org/W3173572290","https://openalex.org/W3177214747"],"related_works":["https://openalex.org/W4323768008","https://openalex.org/W1941703695","https://openalex.org/W3131574667","https://openalex.org/W2368997734","https://openalex.org/W4360995134","https://openalex.org/W4248382324","https://openalex.org/W3023605104","https://openalex.org/W2039473718","https://openalex.org/W2387529410","https://openalex.org/W2077561982"],"abstract_inverted_index":{"The":[0],"ubiquity":[1],"of":[2,9,18,72,130,142,166],"mobile":[3],"devices":[4],"and":[5,41,74,106,121,135,157,164],"the":[6,69,77,91,111,117,140,143,161,167],"accompanying":[7],"deployment":[8],"sensing":[10],"technologies":[11],"have":[12],"resulted":[13],"in":[14,124],"a":[15,48,63,104],"massive":[16],"amount":[17],"trajectory":[19,26,43,97],"data.":[20],"One":[21],"important":[22],"fundamental":[23],"task":[24],"is":[25,30],"similarity":[27,44,98],"computation,":[28,45,99],"which":[29,159],"to":[31,67,138],"determine":[32],"how":[33],"similar":[34],"two":[35,128,151],"trajectories":[36,73,80],"are.":[37],"To":[38],"enable":[39],"effective":[40],"efficient":[42],"we":[46,61,126],"propose":[47],"novel":[49],"robust":[50],"model,":[51],"namely":[52],"<u>C</u>ontrastive":[53],"<u>L</u>earning":[54],"based":[55,81],"<u>T</u>rajectory":[56],"<u>Sim</u>ilarity":[57],"Computation":[58],"(CL-TSim).":[59],"Specifically,":[60],"employ":[62],"contrastive":[64],"learning":[65,94],"mechanism":[66],"learn":[68],"latent":[70],"representations":[71],"then":[75],"calculate":[76],"dissimilarity":[78],"between":[79],"on":[82,150],"these":[83],"representations.":[84],"Compared":[85],"with":[86],"sequential":[87],"auto-encoders":[88],"that":[89],"are":[90,148],"mainstream":[92],"deep":[93],"architectures":[95],"for":[96],"CL-TSim":[100],"does":[101],"not":[102],"require":[103],"decoder":[105],"step-by-step":[107],"reconstruction,":[108],"thus":[109],"improving":[110],"training":[112],"efficiency":[113,165],"significantly.":[114],"Moreover,":[115],"considering":[116],"non-uniform":[118],"sampling":[119],"rate":[120],"noisy":[122],"points":[123],"trajectories,":[125],"adopt":[127],"type":[129],"augmentations,":[131],"i.e.,":[132,155],"point":[133,136],"dowm-sampling":[134],"distorting,":[137],"enhance":[139],"robustness":[141],"proposed":[144,168],"model.":[145,169],"Extensive":[146],"experiments":[147],"conducted":[149],"widely-used":[152],"real-world":[153],"datasets,":[154],"Porto":[156],"ChengDu,":[158],"demonstrate":[160],"superior":[162],"effectiveness":[163]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":7}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}