{"id":"https://openalex.org/W4205848941","doi":"https://doi.org/10.1145/3467977","title":"Analyzing Trajectory Gaps to Find Possible Rendezvous Region","display_name":"Analyzing Trajectory Gaps to Find Possible Rendezvous Region","publication_year":2022,"publication_date":"2022-01-18","ids":{"openalex":"https://openalex.org/W4205848941","doi":"https://doi.org/10.1145/3467977"},"language":"en","primary_location":{"id":"doi:10.1145/3467977","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3467977","pdf_url":null,"source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","raw_type":"journal-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/A5047020818","display_name":"Arun Sharma","orcid":"https://orcid.org/0000-0002-6908-6960"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Arun Sharma","raw_affiliation_strings":["University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA"],"affiliations":[{"raw_affiliation_string":"University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA","institution_ids":["https://openalex.org/I4210101327","https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102940260","display_name":"Shashi Shekhar","orcid":"https://orcid.org/0000-0002-3191-3879"},"institutions":[{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]},{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shashi Shekhar","raw_affiliation_strings":["University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA"],"affiliations":[{"raw_affiliation_string":"University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA","institution_ids":["https://openalex.org/I4210101327","https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5047020818"],"corresponding_institution_ids":["https://openalex.org/I130238516","https://openalex.org/I4210101327"],"apc_list":null,"apc_paid":null,"fwci":1.4873,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.80734873,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"13","issue":"3","first_page":"1","last_page":"23"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9983999729156494,"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":0.9983999729156494,"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/T11622","display_name":"Maritime Navigation and Safety","score":0.9972000122070312,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9865999817848206,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/rendezvous","display_name":"Rendezvous","score":0.9570754766464233},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8472741842269897},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7019730806350708},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.7000607848167419},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.6477673053741455},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5965901613235474},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4948992133140564},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4346110224723816},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.4101145267486572},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3986046314239502},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33882471919059753},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33068686723709106},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.14166250824928284}],"concepts":[{"id":"https://openalex.org/C2779968344","wikidata":"https://www.wikidata.org/wiki/Q3932925","display_name":"Rendezvous","level":3,"score":0.9570754766464233},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8472741842269897},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7019730806350708},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.7000607848167419},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.6477673053741455},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5965901613235474},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4948992133140564},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4346110224723816},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.4101145267486572},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3986046314239502},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33882471919059753},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33068686723709106},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.14166250824928284},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/C29829512","wikidata":"https://www.wikidata.org/wiki/Q40218","display_name":"Spacecraft","level":2,"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3467977","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3467977","pdf_url":null,"source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"display_name":"Life below water","id":"https://metadata.un.org/sdg/14"}],"awards":[{"id":"https://openalex.org/G6935338699","display_name":null,"funder_award_id":"HM0476-20-1-0009","funder_id":"https://openalex.org/F4320332165","funder_display_name":"National Geospatial-Intelligence Agency"}],"funders":[{"id":"https://openalex.org/F4320332165","display_name":"National Geospatial-Intelligence Agency","ror":"https://ror.org/02k4pxv54"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1552408883","https://openalex.org/W1978375645","https://openalex.org/W1997426143","https://openalex.org/W2001915286","https://openalex.org/W2013333366","https://openalex.org/W2029149715","https://openalex.org/W2042858525","https://openalex.org/W2074573550","https://openalex.org/W2106659141","https://openalex.org/W2115857176","https://openalex.org/W2117895438","https://openalex.org/W2118371392","https://openalex.org/W2127336753","https://openalex.org/W2134268609","https://openalex.org/W2576109540","https://openalex.org/W2613103384","https://openalex.org/W2751694342"],"related_works":["https://openalex.org/W2057371520","https://openalex.org/W2807763113","https://openalex.org/W2542862126","https://openalex.org/W2030068303","https://openalex.org/W1521763702","https://openalex.org/W2245527669","https://openalex.org/W937816491","https://openalex.org/W2046042302","https://openalex.org/W2089952735","https://openalex.org/W2906790212"],"abstract_inverted_index":{"Given":[0],"trajectory":[1,35,243],"data":[2,36,141,244],"with":[3,132,231],"gaps,":[4],"we":[5,107,127,162],"investigate":[6],"methods":[7,59],"to":[8,40,64,81,119,155,182],"identify":[9,41],"possible":[10,216],"rendezvous":[11,72,87,122,174,217],"regions.":[12,123],"The":[13,26],"problem":[14],"has":[15],"societal":[16],"applications":[17],"such":[18,66],"as":[19,153],"improving":[20],"maritime":[21,242],"safety":[22],"and":[23,95,116,135,176,199,210,228,240,256,270,278],"regulatory":[24],"enforcement.":[25],"challenges":[27],"come":[28],"from":[29,77],"two":[30,189],"aspects.":[31],"First,":[32],"gaps":[33,94,115],"in":[34,70],"make":[37],"it":[38],"difficult":[39],"regions":[42,88],"where":[43],"moving":[44],"objects":[45,69],"may":[46,60,73],"have":[47,74],"rendezvoused":[48],"for":[49,170,214],"nefarious":[50],"reasons.":[51],"Hence,":[52],"traditional":[53],"linear":[54],"or":[55],"shortest":[56],"path":[57],"interpolation":[58],"not":[61],"be":[62],"able":[63],"detect":[65],"activities,":[67],"since":[68],"a":[71,86,90,109,164,172,194,201,221,232],"traveled":[75],"away":[76],"their":[78],"usual":[79],"routes":[80],"meet.":[82],"Second,":[83],"user":[84],"detecting":[85],"involve":[89],"large":[91],"number":[92],"of":[93,113,224],"associated":[96],"trajectories,":[97],"making":[98],"the":[99,144,156,208,225,247,252,260],"task":[100],"computationally":[101],"very":[102],"expensive.":[103],"In":[104,124,159],"preliminary":[105],"work,":[106],"proposed":[108,211,248,277],"more":[110],"effective":[111],"way":[112],"handling":[114],"provided":[117],"examples":[118],"illustrate":[120],"potential":[121,173],"this":[125,160],"article,":[126,161],"are":[128],"providing":[129],"detailed":[130],"experiments":[131,266],"both":[133,276],"synthetic":[134,140,239,273],"real-world":[136,241],"data.":[137],"Experiments":[138],"on":[139,238,268,272,275],"show":[142,245],"that":[143,246],"accuracy":[145,269],"improved":[146],"by":[147],"50":[148],"percent,":[149],"which":[150],"is":[151],"substantial":[152],"compared":[154],"baseline":[157,209,261,279],"approach.":[158],"propose":[163],"refined":[165],"algorithm":[166],"Temporal":[167],"Selection":[168],"Search":[169],"finding":[171,177],"region":[175],"an":[178],"optimal":[179],"temporal":[180],"range":[181],"improve":[183],"computational":[184],"efficiency.":[185],"We":[186,219,263],"also":[187,264],"incorporate":[188],"novel":[190],"spatial":[191],"filters:":[192],"(i)":[193],"Static":[195],"Ellipse":[196],"Intersection":[197,204],"Filter":[198],"(ii)":[200],"Dynamic":[202],"Circle":[203],"Spatial":[205],"Filter.":[206],"Both":[207],"approaches":[212],"account":[213],"every":[215],"pattern.":[218],"provide":[220],"theoretical":[222],"evaluation":[223],"algorithms":[226],"correctness":[227],"completeness":[229],"along":[230],"time":[233,258],"complexity":[234],"analysis.":[235],"Experimental":[236],"results":[237],"approach":[249],"substantially":[250],"improves":[251],"area":[253],"pruning":[254],"effectiveness":[255],"computation":[257],"over":[259],"technique.":[262],"performed":[265],"based":[267],"precision":[271],"dataset":[274],"techniques.":[280]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
