{"id":"https://openalex.org/W2000205028","doi":"https://doi.org/10.1145/2505821.2505824","title":"Finding frequent sub-trajectories with time constraints","display_name":"Finding frequent sub-trajectories with time constraints","publication_year":2013,"publication_date":"2013-08-11","ids":{"openalex":"https://openalex.org/W2000205028","doi":"https://doi.org/10.1145/2505821.2505824","mag":"2000205028"},"language":"en","primary_location":{"id":"doi:10.1145/2505821.2505824","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2505821.2505824","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing","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/A5100667170","display_name":"Xin Huang","orcid":"https://orcid.org/0000-0003-4401-0481"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Huang","raw_affiliation_strings":["Chinese Academy of Sciences, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106731907","display_name":"Jun Luo","orcid":"https://orcid.org/0000-0002-2032-0381"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Luo","raw_affiliation_strings":["Chinese Academy of Sciences, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103325587","display_name":"Xin Wang","orcid":"https://orcid.org/0000-0002-5592-6228"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xin Wang","raw_affiliation_strings":["University of Calgary, Canada","University of CALGARY, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Calgary, Canada","institution_ids":["https://openalex.org/I168635309"]},{"raw_affiliation_string":"University of CALGARY, Canada","institution_ids":["https://openalex.org/I168635309"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6442,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.67344111,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12016","display_name":"Web Data Mining and Analysis","score":0.986299991607666,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.7745327949523926},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7573356628417969},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5910802483558655},{"id":"https://openalex.org/keywords/suffix-tree","display_name":"Suffix tree","score":0.55695641040802},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5246998071670532},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5080225467681885},{"id":"https://openalex.org/keywords/usable","display_name":"USable","score":0.47476744651794434},{"id":"https://openalex.org/keywords/time-complexity","display_name":"Time complexity","score":0.46602603793144226},{"id":"https://openalex.org/keywords/dbscan","display_name":"DBSCAN","score":0.45560163259506226},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.43306270241737366},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3484734296798706},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.3445000946521759},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.3181939721107483},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2975323796272278},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1494564414024353}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7745327949523926},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7573356628417969},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5910802483558655},{"id":"https://openalex.org/C2781166958","wikidata":"https://www.wikidata.org/wiki/Q1426863","display_name":"Suffix tree","level":3,"score":0.55695641040802},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5246998071670532},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5080225467681885},{"id":"https://openalex.org/C2780615836","wikidata":"https://www.wikidata.org/wiki/Q2471869","display_name":"USable","level":2,"score":0.47476744651794434},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.46602603793144226},{"id":"https://openalex.org/C46576248","wikidata":"https://www.wikidata.org/wiki/Q1114630","display_name":"DBSCAN","level":5,"score":0.45560163259506226},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.43306270241737366},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3484734296798706},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.3445000946521759},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.3181939721107483},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2975323796272278},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1494564414024353},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.0},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2505821.2505824","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2505821.2505824","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W180571615","https://openalex.org/W1491450013","https://openalex.org/W1581745374","https://openalex.org/W1588585567","https://openalex.org/W1673310716","https://openalex.org/W1822191625","https://openalex.org/W1966958766","https://openalex.org/W1981398125","https://openalex.org/W1990061958","https://openalex.org/W1995103535","https://openalex.org/W2002564706","https://openalex.org/W2012580531","https://openalex.org/W2016219933","https://openalex.org/W2042968733","https://openalex.org/W2047216628","https://openalex.org/W2059513841","https://openalex.org/W2075190119","https://openalex.org/W2085121383","https://openalex.org/W2094718590","https://openalex.org/W2109182426","https://openalex.org/W2115639613","https://openalex.org/W2127218421","https://openalex.org/W2157734830","https://openalex.org/W2160642098","https://openalex.org/W2167686542","https://openalex.org/W2299467264","https://openalex.org/W2405329296","https://openalex.org/W2500657807","https://openalex.org/W2533248932","https://openalex.org/W2566910703"],"related_works":["https://openalex.org/W1746392762","https://openalex.org/W2159613260","https://openalex.org/W1495956867","https://openalex.org/W2003608043","https://openalex.org/W2549663625","https://openalex.org/W1975060495","https://openalex.org/W2741342861","https://openalex.org/W4383468830","https://openalex.org/W2024147613","https://openalex.org/W2064184672"],"abstract_inverted_index":{"With":[0],"the":[1,19,63,70,92,96,103,111,121,129,138,142,150,170],"advent":[2],"of":[3,29],"location-based":[4],"social":[5],"media":[6],"and":[7,15,98,162,166],"location-acquisition":[8],"technologies,":[9],"trajectory":[10,50],"data":[11],"are":[12,152],"becoming":[13],"more":[14,16],"ubiquitous":[17],"in":[18,31,36,74],"real":[20],"world.":[21],"Trajectory":[22],"pattern":[23,51],"mining":[24],"has":[25],"received":[26],"a":[27,48,79],"lot":[28],"attention":[30],"recent":[32],"years.":[33],"Frequent":[34],"sub-trajectories,":[35],"particular,":[37],"might":[38],"contain":[39],"very":[40],"usable":[41],"knowledge.":[42],"In":[43],"this":[44],"paper,":[45],"we":[46,90,116],"define":[47],"new":[49],"called":[52],"frequent":[53,112,123,143],"sub-trajectories":[54,119,144],"with":[55,120,126,145],"time":[56,73,131,146],"constraints":[57],"(FSTTC)":[58],"that":[59,157],"requires":[60],"not":[61],"only":[62],"same":[64,122],"continuous":[65],"location":[66,100,113,124],"sequence":[67,125],"but":[68],"also":[69],"similar":[71],"staying":[72,130],"each":[75],"location.":[76],"We":[77],"present":[78],"two-phase":[80],"approach":[81,159],"to":[82,108,128,136],"find":[83,137,164],"FSTTCs":[84],"based":[85],"on":[86],"suffix":[87,104],"tree.":[88],"Firstly,":[89],"select":[91],"spatial":[93],"information":[94,168],"from":[95,169],"trajectories":[97],"generate":[99],"sequences.":[101,114],"Then":[102],"tree":[105],"is":[106,160],"adopted":[107],"mine":[109],"out":[110],"Secondly,":[115],"cluster":[117],"all":[118],"respect":[127],"using":[132],"modified":[133],"DBSCAN":[134],"algorithm":[135],"densest":[139],"clusters.":[140],"Accordingly,":[141],"constraints,":[147],"represented":[148],"by":[149],"clusters,":[151],"identified.":[153],"Experimental":[154],"results":[155],"show":[156],"our":[158],"efficient":[161],"can":[163],"useful":[165],"interesting":[167],"spatio-temporal":[171],"trajectories.":[172]},"counts_by_year":[{"year":2019,"cited_by_count":2},{"year":2014,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
