{"id":"https://openalex.org/W2902154084","doi":"https://doi.org/10.1109/icpr.2018.8546103","title":"Scalable kNN Search Approximation for Time Series Data","display_name":"Scalable kNN Search Approximation for Time Series Data","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2902154084","doi":"https://doi.org/10.1109/icpr.2018.8546103","mag":"2902154084"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8546103","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8546103","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","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/A5010973892","display_name":"Souka\u00efna Filali Boubrahimi","orcid":"https://orcid.org/0000-0001-5693-6383"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Soukaina Filali Boubrahimi","raw_affiliation_strings":["Departement of Computer Science, Georgia State University, Atlanta, GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departement of Computer Science, Georgia State University, Atlanta, GA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064065006","display_name":"Ruizhe Ma","orcid":"https://orcid.org/0000-0003-2749-3063"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruizhe Ma","raw_affiliation_strings":["Departement of Computer Science, Georgia State University, Atlanta, GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departement of Computer Science, Georgia State University, Atlanta, GA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043887593","display_name":"Berkay Aydin","orcid":"https://orcid.org/0000-0002-9799-9265"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Berkay Aydin","raw_affiliation_strings":["Departement of Computer Science, Georgia State University, Atlanta, GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departement of Computer Science, Georgia State University, Atlanta, GA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050715780","display_name":"Shah Muhammad Hamdi","orcid":"https://orcid.org/0000-0002-9303-7835"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shah Muhammad Hamdi","raw_affiliation_strings":["Departement of Computer Science, Georgia State University, Atlanta, GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departement of Computer Science, Georgia State University, Atlanta, GA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009847987","display_name":"Rafal A. Angryk","orcid":"https://orcid.org/0000-0001-9598-8207"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rafal Angryk","raw_affiliation_strings":["Departement of Computer Science, Georgia State University, Atlanta, GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departement of Computer Science, Georgia State University, Atlanta, GA","institution_ids":["https://openalex.org/I181565077"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181565077"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"970","last_page":"975"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","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/T12205","display_name":"Time Series Analysis and Forecasting","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/T11106","display_name":"Data Management and Algorithms","score":0.9646000266075134,"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/T11309","display_name":"Music and Audio Processing","score":0.9545999765396118,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.7355732321739197},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7221609354019165},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7111465334892273},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6428700685501099},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3982800543308258},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3329552710056305},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2911280393600464},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.12659573554992676}],"concepts":[{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.7355732321739197},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7221609354019165},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7111465334892273},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6428700685501099},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3982800543308258},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3329552710056305},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2911280393600464},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.12659573554992676},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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:10.1109/icpr.2018.8546103","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8546103","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W188174107","https://openalex.org/W1499049447","https://openalex.org/W1989037929","https://openalex.org/W2013657661","https://openalex.org/W2039260438","https://openalex.org/W2040407051","https://openalex.org/W2073459066","https://openalex.org/W2084616221","https://openalex.org/W2086504823","https://openalex.org/W2091921805","https://openalex.org/W2102201884","https://openalex.org/W2108400301","https://openalex.org/W2123049307","https://openalex.org/W2144305663","https://openalex.org/W2155502235","https://openalex.org/W2161621125","https://openalex.org/W2526367648","https://openalex.org/W2537218912","https://openalex.org/W2540083950","https://openalex.org/W2562786159","https://openalex.org/W2585090940","https://openalex.org/W2772387153","https://openalex.org/W2774846488","https://openalex.org/W2775487445","https://openalex.org/W2799718654","https://openalex.org/W2963069035","https://openalex.org/W3099011192","https://openalex.org/W4242702158","https://openalex.org/W6607659811","https://openalex.org/W6629760146","https://openalex.org/W6668990524","https://openalex.org/W6681527806","https://openalex.org/W6682888194","https://openalex.org/W6747093134"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W4235240664","https://openalex.org/W2965083567","https://openalex.org/W1838576100","https://openalex.org/W2095886385","https://openalex.org/W2889616422","https://openalex.org/W3151146928","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"k":[0],"Nearest":[1],"Neighbor":[2],"(":[3],"kNN)":[4],"is":[5,20,103,162],"a":[6,25,51,60,110,134,142],"widely":[7],"used":[8],"classifier":[9,49,168],"in":[10],"time":[11],"series":[12],"data":[13,57],"analytics":[14],"due":[15],"to":[16,23,71,100,114,164,171],"its":[17],"interpretability.":[18],"kNN":[19,48,119,167],"often":[21],"referred":[22],"as":[24,29,83,133],"lazy":[26],"learning":[27],"algorithm":[28],"it":[30,39,66],"does":[31,38],"not":[32],"learn":[33],"any":[34,41],"discriminative":[35],"function":[36],"nor":[37],"generate":[40],"rules":[42],"from":[43],"the":[44,55,96,116,125,129,156,165],"training":[45,56],"data.":[46],"Instead,":[47],"requires":[50],"search":[52,99],"over":[53],"all":[54],"for":[58,73],"classifying":[59],"single":[61],"test":[62],"sample":[63],"which":[64,87],"makes":[65],"computationally":[67],"demanding":[68],"and":[69,150],"hard":[70],"adopt":[72],"real":[74],"world":[75],"application.":[76],"These":[77],"applications":[78],"are,":[79],"sometimes,":[80],"time-critical":[81],"such":[82],"solar":[84],"flare":[85],"prediction":[86],"might":[88],"have":[89],"irreversible":[90],"impacts":[91],"on":[92,141],"Earth.":[93],"Therefore,":[94],"scaling":[95],"nearest":[97,126],"neighbors":[98],"large":[101],"datasets":[102,146],"crucial.":[104],"In":[105],"this":[106],"paper,":[107],"we":[108],"propose":[109],"new":[111],"scalable":[112],"methodology":[113],"mitigate":[115],"problem":[117],"of":[118,131,145,158],"high":[120],"computational":[121],"cost":[122],"by":[123],"approximating":[124],"neighbor(s)":[127],"with":[128,147,169],"help":[130],"clustering":[132],"preprocessing":[135],"step.":[136],"We":[137],"tested":[138],"our":[139,159],"idea":[140],"comprehensive":[143],"set":[144],"varying":[148],"sizes":[149],"labels.":[151],"Our":[152],"results":[153],"show":[154],"that":[155],"performance":[157],"approximate":[160],"technique":[161],"comparable":[163],"exact":[166],"up":[170],"10x":[172],"speed-up.":[173]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}