{"id":"https://openalex.org/W1985119574","doi":"https://doi.org/10.1145/2525314.2525351","title":"Efficient identification and approximation of k-nearest moving neighbors","display_name":"Efficient identification and approximation of k-nearest moving neighbors","publication_year":2013,"publication_date":"2013-11-05","ids":{"openalex":"https://openalex.org/W1985119574","doi":"https://doi.org/10.1145/2525314.2525351","mag":"1985119574"},"language":"en","primary_location":{"id":"doi:10.1145/2525314.2525351","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2525314.2525351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"type":"conference-paper","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/A5038763103","display_name":"\u0393\u03b5\u03ce\u03c1\u03b3\u03b9\u03bf\u03c2 \u03a3\u03ba\u03bf\u03cd\u03bc\u03b1\u03c2","orcid":"https://orcid.org/0000-0001-6475-8484"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Georgios Skoumas","raw_affiliation_strings":["National Technical University of Athens, Greece",", National Technical University of Athens, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Technical University of Athens, Greece","institution_ids":["https://openalex.org/I174458059"]},{"raw_affiliation_string":", National Technical University of Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087768208","display_name":"Dimitrios Skoutas","orcid":"https://orcid.org/0000-0002-6118-5227"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dimitrios Skoutas","raw_affiliation_strings":["Institute for the Management of Information Systems, R.C. Athena"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for the Management of Information Systems, R.C. Athena","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016282282","display_name":"Alexandra Vlachaki","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alexandra Vlachaki","raw_affiliation_strings":["Institute for the Management of Information Systems, R.C. Athena"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for the Management of Information Systems, R.C. Athena","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"264","last_page":"273"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9896000027656555,"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"}},{"id":"https://openalex.org/T10757","display_name":"Geographic Information Systems Studies","score":0.9861000180244446,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"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/computer-science","display_name":"Computer science","score":0.7472249269485474},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.7313255071640015},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.7001561522483826},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6517921686172485},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5693074464797974},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5690160393714905},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4951693117618561},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.49172261357307434},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.4463132619857788},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.4133450984954834},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.396731972694397},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3910287022590637},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36748969554901123},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18132448196411133},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15426695346832275}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7472249269485474},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.7313255071640015},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.7001561522483826},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6517921686172485},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5693074464797974},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5690160393714905},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4951693117618561},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.49172261357307434},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.4463132619857788},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4133450984954834},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.396731972694397},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3910287022590637},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36748969554901123},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18132448196411133},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15426695346832275},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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:10.1145/2525314.2525351","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2525314.2525351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.46000000834465027,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1486723877","https://openalex.org/W1536861392","https://openalex.org/W1542804150","https://openalex.org/W1600584489","https://openalex.org/W1934562893","https://openalex.org/W1981398125","https://openalex.org/W1982483361","https://openalex.org/W1982911127","https://openalex.org/W1995487411","https://openalex.org/W2027752285","https://openalex.org/W2028618575","https://openalex.org/W2031674781","https://openalex.org/W2033626772","https://openalex.org/W2035241283","https://openalex.org/W2044023374","https://openalex.org/W2045928315","https://openalex.org/W2046466133","https://openalex.org/W2049657873","https://openalex.org/W2060297659","https://openalex.org/W2062231365","https://openalex.org/W2074104866","https://openalex.org/W2076014932","https://openalex.org/W2090667601","https://openalex.org/W2090852828","https://openalex.org/W2112877387","https://openalex.org/W2118371392","https://openalex.org/W2120320296","https://openalex.org/W2122430112","https://openalex.org/W2141136363","https://openalex.org/W2147880780","https://openalex.org/W2151573792","https://openalex.org/W2165169065","https://openalex.org/W2172041433","https://openalex.org/W2666600683","https://openalex.org/W4212848460","https://openalex.org/W4247453596","https://openalex.org/W4256046779","https://openalex.org/W4285719527","https://openalex.org/W4301891957"],"related_works":["https://openalex.org/W4323768008","https://openalex.org/W1941703695","https://openalex.org/W4248382324","https://openalex.org/W3131574667","https://openalex.org/W4360995134","https://openalex.org/W2373557848","https://openalex.org/W2088970451","https://openalex.org/W2002488624","https://openalex.org/W2157008402","https://openalex.org/W2592302855"],"abstract_inverted_index":{"Nowadays,":[0],"massive":[1],"amounts":[2],"of":[3,9,23,44,61,100,151,165,173],"tracking":[4],"data":[5,25],"for":[6,28,74],"various":[7],"types":[8],"moving":[10,72],"objects,":[11],"including":[12],"vehicles,":[13],"humans":[14],"and":[15,33,36,40,79,97,103,158,190],"animals,":[16],"are":[17],"becoming":[18],"available.":[19],"Analyzing":[20],"this":[21,64],"type":[22],"spatio-temporal":[24],"is":[26,47,181],"crucial":[27],"discovering":[29],"movement":[30],"patterns,":[31],"understanding":[32],"forecasting":[34],"behaviors,":[35],"developing":[37],"novel":[38],"applications":[39],"services.":[41],"One":[42],"problem":[43],"particular":[45],"interest":[46],"finding":[48,69],"objects":[49],"that":[50,90],"move":[51],"close":[52],"together":[53],"with":[54],"a":[55,75,87,162],"certain":[56],"object":[57,78],"during":[58],"some":[59],"periods":[60],"time.":[62],"In":[63],"paper,":[65],"we":[66,104,111],"focus":[67,112],"on":[68,113,149,177],"the":[70,84,95,98,101,120,133,138,143,166,174],"k-nearest":[71,167],"neighbors":[73],"given":[76],"query":[77],"time":[80],"interval.":[81],"We":[82],"formulate":[83],"problem,":[85],"using":[86],"similarity":[88],"function":[89],"takes":[91],"into":[92],"consideration":[93],"both":[94],"proximity":[96],"direction":[99],"trajectories,":[102,135],"firstly":[105],"present":[106],"an":[107],"exact":[108],"algorithm.":[109],"Then,":[110],"approximate":[114,132],"algorithms":[115,176],"in":[116,184],"order":[117,185],"to":[118,131,141,160,186],"reduce":[119],"execution":[121],"time,":[122],"investigating":[123],"two":[124],"directions.":[125],"The":[126,146],"first":[127],"employs":[128],"line":[129],"simplification":[130],"compared":[134],"thus":[136],"reducing":[137],"calculations":[139],"needed":[140],"identify":[142],"nearest":[144],"neighbors.":[145,168],"second":[147],"relies":[148],"estimates":[150],"prior":[152],"probabilities":[153],"derived":[154],"from":[155],"trajectory":[156],"distributions":[157],"attempts":[159],"achieve":[161],"faster":[163],"approximation":[164],"A":[169],"detailed":[170],"experimental":[171],"evaluation":[172],"aforementioned":[175],"three":[178],"real-world":[179],"datasets":[180],"finally":[182],"presented":[183],"verify":[187],"their":[188],"efficiency":[189],"accuracy.":[191]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
