{"id":"https://openalex.org/W4317641521","doi":"https://doi.org/10.14778/3565838.3565847","title":"ONe Index for All Kernels (ONIAK)","display_name":"ONe Index for All Kernels (ONIAK)","publication_year":2022,"publication_date":"2022-09-01","ids":{"openalex":"https://openalex.org/W4317641521","doi":"https://doi.org/10.14778/3565838.3565847"},"language":"en","primary_location":{"id":"doi:10.14778/3565838.3565847","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3565838.3565847","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"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":"Proceedings of the VLDB Endowment","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/A5013337954","display_name":"Jingfan Meng","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingfan Meng","raw_affiliation_strings":["Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012792241","display_name":"Huayi Wang","orcid":"https://orcid.org/0000-0001-6274-3844"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huayi Wang","raw_affiliation_strings":["Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025728584","display_name":"Jun Xu","orcid":"https://orcid.org/0000-0002-0046-8119"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Xu","raw_affiliation_strings":["Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019383096","display_name":"Mitsunori Ogihara","orcid":"https://orcid.org/0000-0002-5690-7854"},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mitsunori Ogihara","raw_affiliation_strings":["University of Miami"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Miami","institution_ids":["https://openalex.org/I145608581"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2936,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.54710097,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"15","issue":"13","first_page":"3937","last_page":"3949"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9991999864578247,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9839000105857849,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.7966324687004089},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7073588967323303},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.6618936061859131},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.5320392847061157},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.43216168880462646},{"id":"https://openalex.org/keywords/quadratic-equation","display_name":"Quadratic equation","score":0.4108172357082367},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4080042541027069},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23370787501335144},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22882646322250366}],"concepts":[{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.7966324687004089},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7073588967323303},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.6618936061859131},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5320392847061157},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.43216168880462646},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.4108172357082367},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4080042541027069},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23370787501335144},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22882646322250366},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14778/3565838.3565847","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3565838.3565847","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"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":"Proceedings of the VLDB Endowment","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W117514602","https://openalex.org/W140822990","https://openalex.org/W642889137","https://openalex.org/W1540570089","https://openalex.org/W1632694667","https://openalex.org/W2008995227","https://openalex.org/W2062112832","https://openalex.org/W2093813380","https://openalex.org/W2157575532","https://openalex.org/W2162006472","https://openalex.org/W2294518132","https://openalex.org/W2330471278","https://openalex.org/W2612972698","https://openalex.org/W2763008059","https://openalex.org/W2913059114","https://openalex.org/W2963265099","https://openalex.org/W2964084429","https://openalex.org/W2972555443","https://openalex.org/W3007299504","https://openalex.org/W3030386564","https://openalex.org/W3175564083"],"related_works":["https://openalex.org/W1873761914","https://openalex.org/W1600993223","https://openalex.org/W2372694090","https://openalex.org/W2348101466","https://openalex.org/W2753337109","https://openalex.org/W1592893681","https://openalex.org/W2111308187","https://openalex.org/W1991645216","https://openalex.org/W2413339343","https://openalex.org/W2122688963"],"abstract_inverted_index":{"In":[0,23,126],"this":[1,194],"work,":[2],"we":[3,25,88],"formulate":[4],"and":[5,73,80,95,108,134,174],"solve":[6],"a":[7,31,39,46,51,60,93,128,200,214,219,246],"new":[8],"type":[9],"of":[10,63,181,238],"approximate":[11],"nearest":[12],"neighbor":[13],"search":[14,26],"(ANNS)":[15],"problems":[16,66,112],"called":[17,99,223],"ANNS":[18,65],"after":[19,34],"linear":[20,166],"transformation":[21],"(ALT).":[22],"ANNS-ALT,":[24,83],"for":[27,102,135,137,213],"the":[28,57,114,169,182,186,190,208,232,239],"vector":[29],"(in":[30],"dataset)":[32],"that,":[33,153],"being":[35],"linearly":[36],"transformed":[37],"by":[38,151],"user-specified":[40],"query":[41,47,147,163,176],"matrix,":[42],"is":[43,50,118,131,156,262],"closest":[44],"to":[45,79,106,179],"vector.":[48],"It":[49],"very":[52],"general":[53],"mother":[54,170],"problem":[55,171,204],"in":[56,71],"sense":[58],"that":[59,67,87,143,205,229,255],"wide":[61],"range":[62],"baby":[64,111,187],"have":[68,145],"important":[69],"applications":[70],"databases":[72],"machine":[74],"learning":[75],"can":[76,144,206],"be":[77],"reduced":[78],"solved":[81],"as":[82],"or":[84],"its":[85,110],"dual":[86],"call":[89],"ANNS-ALTD.":[90],"We":[91,149,217,243],"propose":[92,218,245],"novel":[94,220],"computationally":[96],"efficient":[97],"solution,":[98],"ONe":[100],"Index":[101],"All":[103],"Kernels":[104],"(ONIAK),":[105],"ANNS-ALT":[107,141,251],"all":[109,139],"when":[113,154,260],"data":[115],"dimension":[116,202,240],"d":[117,123,155,261],"not":[119,157],"too":[120,158],"large":[121,215],"(say":[122],"\u2264":[124],"200).":[125],"ONIAK,":[127],"universal":[129,195],"index":[130,196],"built,":[132],"once":[133],"all,":[136],"answering":[138],"future":[140],"queries":[142],"distinct":[146],"matrices.":[148],"show":[150],"experiments":[152],"large,":[159],"ONIAK":[160],"has":[161,175],"better":[162],"performance":[164],"than":[165],"scan":[167],"on":[168,185],"(of":[172],"ANNS-ALT),":[173],"performances":[177],"comparable":[178],"those":[180],"state-of-the-art":[183],"solutions":[184],"problems.":[188],"However,":[189],"algorithmic":[191,221],"technique":[192],"behind":[193],"approach":[197],"suffers":[198],"from":[199],"so-called":[201],"blowup":[203,241],"make":[207],"indexing":[209,235],"time":[210],"prohibitively":[211],"long":[212,234],"dataset.":[216],"technique,":[222],"fast":[224],"GOE":[225],"quadratic":[226],"form":[227],"(FGoeQF),":[228],"completely":[230],"solves":[231],"(prohibitively":[233],"time)":[236],"fallout":[237],"problem.":[242],"also":[244],"Johnson-Lindenstrauss":[247],"transform":[248],"(JLT)":[249],"based":[250],"(and":[252],"ANNS-ALTD)":[253],"solution":[254],"significantly":[256],"outperforms":[257],"any":[258],"competitor":[259],"large.":[263]},"counts_by_year":[{"year":2024,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}