{"id":"https://openalex.org/W2006555691","doi":"https://doi.org/10.1145/1341012.1341082","title":"TS2-tree - an efficient similarity based organization for trajectory data","display_name":"TS2-tree - an efficient similarity based organization for trajectory data","publication_year":2007,"publication_date":"2007-11-07","ids":{"openalex":"https://openalex.org/W2006555691","doi":"https://doi.org/10.1145/1341012.1341082","mag":"2006555691"},"language":"en","primary_location":{"id":"doi:10.1145/1341012.1341082","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1341012.1341082","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems","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/A5059841252","display_name":"Petko Bakalov","orcid":"https://orcid.org/0000-0003-4322-5624"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Petko Bakalov","raw_affiliation_strings":["University of California, Riverside"],"affiliations":[{"raw_affiliation_string":"University of California, Riverside","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078245746","display_name":"Eamonn Keogh","orcid":"https://orcid.org/0000-0002-4188-3968"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eamonn Keogh","raw_affiliation_strings":["University of California, Riverside"],"affiliations":[{"raw_affiliation_string":"University of California, Riverside","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000947547","display_name":"Vassilis J. Tsotras","orcid":"https://orcid.org/0000-0001-5462-9451"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vassilis J. Tsotras","raw_affiliation_strings":["University of California, Riverside"],"affiliations":[{"raw_affiliation_string":"University of California, Riverside","institution_ids":["https://openalex.org/I103635307"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5059841252"],"corresponding_institution_ids":["https://openalex.org/I103635307"],"apc_list":null,"apc_paid":null,"fwci":0.6334,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.67346168,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9990000128746033,"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":0.9846000075340271,"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":0.8167153596878052},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.8074421286582947},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7641743421554565},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.7304326295852661},{"id":"https://openalex.org/keywords/range-query","display_name":"Range query (database)","score":0.6391505002975464},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.6004574298858643},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.558466911315918},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5323142409324646},{"id":"https://openalex.org/keywords/database-index","display_name":"Database index","score":0.5176375508308411},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5073787569999695},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.46203258633613586},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.4596312940120697},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.4555240571498871},{"id":"https://openalex.org/keywords/sargable","display_name":"Sargable","score":0.21745580434799194},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.2050551176071167},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2019595205783844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1986490786075592},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.1463594138622284},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12587040662765503},{"id":"https://openalex.org/keywords/web-search-query","display_name":"Web search query","score":0.10410359501838684}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8167153596878052},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.8074421286582947},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7641743421554565},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7304326295852661},{"id":"https://openalex.org/C136736807","wikidata":"https://www.wikidata.org/wiki/Q818943","display_name":"Range query (database)","level":5,"score":0.6391505002975464},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.6004574298858643},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.558466911315918},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5323142409324646},{"id":"https://openalex.org/C59276292","wikidata":"https://www.wikidata.org/wiki/Q580427","display_name":"Database index","level":3,"score":0.5176375508308411},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5073787569999695},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.46203258633613586},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.4596312940120697},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.4555240571498871},{"id":"https://openalex.org/C192939062","wikidata":"https://www.wikidata.org/wiki/Q104840822","display_name":"Sargable","level":4,"score":0.21745580434799194},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2050551176071167},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2019595205783844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1986490786075592},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.1463594138622284},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12587040662765503},{"id":"https://openalex.org/C164120249","wikidata":"https://www.wikidata.org/wiki/Q995982","display_name":"Web search query","level":3,"score":0.10410359501838684},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1341012.1341082","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1341012.1341082","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.6000000238418579}],"awards":[{"id":"https://openalex.org/G1826850654","display_name":null,"funder_award_id":"IIS-0534781","funder_id":"https://openalex.org/F4320337389","funder_display_name":"Division of Information and Intelligent Systems"}],"funders":[{"id":"https://openalex.org/F4320337389","display_name":"Division of Information and Intelligent Systems","ror":"https://ror.org/053a2cp42"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W1536861392","https://openalex.org/W1939649909","https://openalex.org/W1989037929","https://openalex.org/W1990997812","https://openalex.org/W2115857176","https://openalex.org/W2163203501"],"related_works":["https://openalex.org/W1949910768","https://openalex.org/W2254397067","https://openalex.org/W2405216906","https://openalex.org/W924614198","https://openalex.org/W1505866794","https://openalex.org/W1882921205","https://openalex.org/W1480566255","https://openalex.org/W2013685631","https://openalex.org/W1519492375","https://openalex.org/W2593823386"],"abstract_inverted_index":{"The":[0,90],"increasingly":[1],"popular":[2],"GPS":[3],"technology":[4],"and":[5,23,53,84,97],"the":[6,15,98],"growing":[7],"amount":[8],"of":[9,26,74,100],"trajectory":[10,42,76],"data":[11,43],"it":[12],"generates":[13],"create":[14],"need":[16],"for":[17,40,68],"developing":[18],"applications":[19],"that":[20],"efficiently":[21],"store":[22],"query":[24,83,94],"trajectories":[25],"moving":[27],"objects.":[28],"In":[29],"this":[30],"paper":[31],"we":[32,63],"introduce":[33],"TS2":[34,49],"tree,":[35],"a":[36,65,71],"novel":[37],"indexing":[38],"structure":[39],"organizing":[41],"based":[44,60],"on":[45,56,61],"similarity":[46,80,85],"between":[47,58],"trajectories.":[48],"tree":[50],"provides":[51],"lower":[52],"upper":[54],"bounds":[55],"distance":[57],"trajectories,":[59],"which":[62],"propose":[64],"general":[66],"framework":[67],"effectively":[69],"answering":[70],"wide":[72],"range":[73],"similarity-based":[75],"queries":[77],"such":[78],"as":[79],"threshold":[81],"(ST)":[82],"best":[86],"fit":[87],"(SBF)":[88],"query.":[89],"multifold":[91],"reduction":[92],"in":[93],"computation":[95],"times":[96],"number":[99],"I/O":[101],"operations":[102],"is":[103],"demonstrated":[104],"through":[105],"an":[106],"extensive":[107],"experimental":[108],"evaluation.":[109]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}