{"id":"https://openalex.org/W1567097384","doi":"https://doi.org/10.1109/icde.2015.7113351","title":"Indexing and matching trajectories under inconsistent sampling rates","display_name":"Indexing and matching trajectories under inconsistent sampling rates","publication_year":2015,"publication_date":"2015-04-01","ids":{"openalex":"https://openalex.org/W1567097384","doi":"https://doi.org/10.1109/icde.2015.7113351","mag":"1567097384"},"language":"en","primary_location":{"id":"doi:10.1109/icde.2015.7113351","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2015.7113351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 31st International Conference on Data Engineering","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pureadmin.qub.ac.uk/ws/files/17977937/icde15.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054697900","display_name":"Sayan Ranu","orcid":"https://orcid.org/0000-0003-4147-9372"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"education","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sayan Ranu","raw_affiliation_strings":["Dept. of CSE, IIT Madras, Chennai, India","Dept. of CSE, IIT - Madras, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of CSE, IIT Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]},{"raw_affiliation_string":"Dept. of CSE, IIT - Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113740386","display_name":"P Deepak","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Deepak P","raw_affiliation_strings":["IBM Research, Bangalore, India","IBM Research, Manyata Tech. Park, Bangalore, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research, Bangalore, India","institution_ids":["https://openalex.org/I4210103279"]},{"raw_affiliation_string":"IBM Research, Manyata Tech. Park, Bangalore, India","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022555817","display_name":"Aditya Telang","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Aditya D. Telang","raw_affiliation_strings":["IBM Research, Bangalore, India","IBM Research, Manyata Tech. Park, Bangalore, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research, Bangalore, India","institution_ids":["https://openalex.org/I4210103279"]},{"raw_affiliation_string":"IBM Research, Manyata Tech. Park, Bangalore, India","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065031367","display_name":"Prasad Deshpande","orcid":"https://orcid.org/0000-0001-6389-533X"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Prasad Deshpande","raw_affiliation_strings":["IBM Research, Bangalore, India","IBM Research, Manyata Tech. Park, Bangalore, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research, Bangalore, India","institution_ids":["https://openalex.org/I4210103279"]},{"raw_affiliation_string":"IBM Research, Manyata Tech. Park, Bangalore, India","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113793867","display_name":"Sriram Raghavan","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Sriram Raghavan","raw_affiliation_strings":["IBM Research, Bangalore, India","IBM Research, Manyata Tech. Park, Bangalore, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research, Bangalore, India","institution_ids":["https://openalex.org/I4210103279"]},{"raw_affiliation_string":"IBM Research, Manyata Tech. Park, Bangalore, India","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.8588,"has_fulltext":true,"cited_by_count":136,"citation_normalized_percentile":{"value":0.98550808,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"999","last_page":"1010"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9994000196456909,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9768000245094299,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.7459337115287781},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.7378659844398499},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6361482739448547},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.6042630076408386},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5751550793647766},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5685741901397705},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.5590909123420715},{"id":"https://openalex.org/keywords/lipschitz-continuity","display_name":"Lipschitz continuity","score":0.531762421131134},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.4585570693016052},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.45023852586746216},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40576764941215515},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3464946746826172},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.325469046831131},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25937801599502563},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.14149999618530273},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.12132835388183594},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10444533824920654}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7459337115287781},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.7378659844398499},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6361482739448547},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.6042630076408386},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5751550793647766},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5685741901397705},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.5590909123420715},{"id":"https://openalex.org/C22324862","wikidata":"https://www.wikidata.org/wiki/Q652707","display_name":"Lipschitz continuity","level":2,"score":0.531762421131134},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.4585570693016052},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.45023852586746216},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40576764941215515},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3464946746826172},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.325469046831131},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25937801599502563},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.14149999618530273},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.12132835388183594},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10444533824920654},{"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/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/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"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":2,"locations":[{"id":"doi:10.1109/icde.2015.7113351","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2015.7113351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 31st International Conference on Data Engineering","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.qub.ac.uk/portal:publications/b548ef90-8c7c-4b28-ba2c-160b8c1c13e1","is_oa":true,"landing_page_url":"https://pure.qub.ac.uk/en/publications/b548ef90-8c7c-4b28-ba2c-160b8c1c13e1","pdf_url":"https://pureadmin.qub.ac.uk/ws/files/17977937/icde15.pdf","source":{"id":"https://openalex.org/S4306402319","display_name":"Research Portal (Queen's University Belfast)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126231945","host_organization_name":"Queen's University Belfast","host_organization_lineage":["https://openalex.org/I126231945"],"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":"Ranu , S , Padmanabhan , D , Telang , A D , Deshpande , P &amp; Raghavan , S 2015 , Indexing and matching trajectories under inconsistent sampling rates . in Proceedings of the 2015 IEEE 31st International Conference on Data Engineering, ICDE 2015 . Institute of Electrical and Electronics Engineers Inc. , pp. 999-1010 , 2015 IEEE 31st International Conference on Data Engineering (ICDE) , Seoul , Korea, Republic of , 13/04/2015 . https://doi.org/10.1109/ICDE.2015.7113351","raw_type":"contributionToPeriodical"}],"best_oa_location":{"id":"pmh:oai:pure.qub.ac.uk/portal:publications/b548ef90-8c7c-4b28-ba2c-160b8c1c13e1","is_oa":true,"landing_page_url":"https://pure.qub.ac.uk/en/publications/b548ef90-8c7c-4b28-ba2c-160b8c1c13e1","pdf_url":"https://pureadmin.qub.ac.uk/ws/files/17977937/icde15.pdf","source":{"id":"https://openalex.org/S4306402319","display_name":"Research Portal (Queen's University Belfast)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126231945","host_organization_name":"Queen's University Belfast","host_organization_lineage":["https://openalex.org/I126231945"],"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":"Ranu , S , Padmanabhan , D , Telang , A D , Deshpande , P &amp; Raghavan , S 2015 , Indexing and matching trajectories under inconsistent sampling rates . in Proceedings of the 2015 IEEE 31st International Conference on Data Engineering, ICDE 2015 . Institute of Electrical and Electronics Engineers Inc. , pp. 999-1010 , 2015 IEEE 31st International Conference on Data Engineering (ICDE) , Seoul , Korea, Republic of , 13/04/2015 . https://doi.org/10.1109/ICDE.2015.7113351","raw_type":"contributionToPeriodical"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W1567097384.pdf","grobid_xml":"https://content.openalex.org/works/W1567097384.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1486723877","https://openalex.org/W1530348622","https://openalex.org/W1597504361","https://openalex.org/W1864972570","https://openalex.org/W1966416504","https://openalex.org/W2008814765","https://openalex.org/W2046466133","https://openalex.org/W2049626361","https://openalex.org/W2063491776","https://openalex.org/W2091921805","https://openalex.org/W2094283130","https://openalex.org/W2100946521","https://openalex.org/W2112877387","https://openalex.org/W2118269922","https://openalex.org/W2118371392","https://openalex.org/W2141596757","https://openalex.org/W2147880780","https://openalex.org/W2166771065","https://openalex.org/W2172041433","https://openalex.org/W4299691394","https://openalex.org/W6629065563","https://openalex.org/W6675130837"],"related_works":["https://openalex.org/W3185235544","https://openalex.org/W2911623553","https://openalex.org/W4297791327","https://openalex.org/W2897842840","https://openalex.org/W2397777611","https://openalex.org/W1502031429","https://openalex.org/W3024364549","https://openalex.org/W2417585376","https://openalex.org/W1994157709","https://openalex.org/W2023595528"],"abstract_inverted_index":{"Quantifying":[0],"the":[1,22,26,29,77,86,113,139,146],"similarity":[2],"between":[3],"two":[4],"trajectories":[5,62],"is":[6,73],"a":[7,16,39,50],"fundamental":[8],"operation":[9],"in":[10,25],"analysis":[11],"of":[12,18,28,35,79,116,148,156],"spatio-temporal":[13],"databases.":[14],"While":[15],"number":[17],"distance":[19,52,141],"functions":[20],"exist,":[21],"recent":[23],"shift":[24],"dynamics":[27],"trajectory":[30,95,126,149],"generation":[31],"procedure":[32],"violates":[33],"one":[34],"their":[36],"core":[37],"assumptions;":[38],"consistent":[40],"and":[41,65],"uniform":[42],"sampling":[43,67],"rate.":[44],"In":[45],"this":[46],"paper,":[47],"we":[48,99],"formulate":[49],"robust":[51],"function":[53],"called":[54,104],"Edit":[55],"Distance":[56],"with":[57,119],"Projections":[58],"(EDwP)":[59],"to":[60,130,133,153],"match":[61],"under":[63],"inconsistent":[64],"variable":[66],"rates":[68],"through":[69],"dynamic":[70],"interpolation.":[71],"This":[72],"achieved":[74],"by":[75,111,151],"deploying":[76],"idea":[78],"projections":[80],"that":[81],"goes":[82],"beyond":[83],"matching":[84],"only":[85],"sampled":[87],"points":[88],"while":[89],"aligning":[90],"trajectories.":[91],"To":[92],"enable":[93],"efficient":[94],"retrievals":[96,150],"using":[97],"EDwP,":[98],"design":[100],"an":[101,154],"index":[102],"structure":[103],"TrajTree.":[105],"TrajTree":[106,144],"derives":[107],"its":[108],"pruning":[109],"power":[110],"employing":[112],"unique":[114],"combination":[115],"bounding":[117],"boxes":[118],"Lipschitz":[120],"embedding.":[121],"Extensive":[122],"experiments":[123],"on":[124],"real":[125],"databases":[127],"demonstrate":[128],"EDwP":[129],"be":[131],"up":[132,152],"5":[134],"times":[135],"more":[136],"accurate":[137],"than":[138],"state-of-the-art":[140],"functions.":[142],"Additionally,":[143],"increases":[145],"efficiency":[147],"order":[155],"magnitude":[157],"over":[158],"existing":[159],"techniques.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":19},{"year":2018,"cited_by_count":17},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
