{"id":"https://openalex.org/W7108994786","doi":"https://doi.org/10.1145/3769843","title":"WoW: A Window-to-Window Incremental Index for Range-Filtering Approximate Nearest Neighbor Search","display_name":"WoW: A Window-to-Window Incremental Index for Range-Filtering Approximate Nearest Neighbor Search","publication_year":2025,"publication_date":"2025-12-04","ids":{"openalex":"https://openalex.org/W7108994786","doi":"https://doi.org/10.1145/3769843"},"language":"en","primary_location":{"id":"doi:10.1145/3769843","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3769843","pdf_url":null,"source":{"id":"https://openalex.org/S4387289859","display_name":"Proceedings of the ACM on Management of Data","issn_l":"2836-6573","issn":["2836-6573"],"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 ACM on Management of Data","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":null,"display_name":"Ziqi Wang","orcid":"https://orcid.org/0009-0003-2027-3524"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziqi Wang","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0003-2027-3524","affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jingzhe Zhang","orcid":"https://orcid.org/0009-0001-7062-9096"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingzhe Zhang","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0001-7062-9096","affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":null,"display_name":"Wei Hu","orcid":"https://orcid.org/0000-0003-3635-6335"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Hu","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-3635-6335","affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":0.9024,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.803858,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"3","issue":"6","first_page":"1","last_page":"27"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.7390999794006348,"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":0.7390999794006348,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.10980000346899033,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.01850000023841858,"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/search-engine-indexing","display_name":"Search engine indexing","score":0.8004000186920166},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.5825999975204468},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.5778999924659729},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5471000075340271},{"id":"https://openalex.org/keywords/range-query","display_name":"Range query (database)","score":0.5450999736785889},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5069000124931335},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4837999939918518},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.46149998903274536},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4390999972820282}],"concepts":[{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.8004000186920166},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5860999822616577},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.5825999975204468},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.5778999924659729},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5471000075340271},{"id":"https://openalex.org/C136736807","wikidata":"https://www.wikidata.org/wiki/Q818943","display_name":"Range query (database)","level":5,"score":0.5450999736785889},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5069000124931335},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4837999939918518},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47920000553131104},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.46149998903274536},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4390999972820282},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43140000104904175},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4212000072002411},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.41780000925064087},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.38600000739097595},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3815000057220459},{"id":"https://openalex.org/C59276292","wikidata":"https://www.wikidata.org/wiki/Q580427","display_name":"Database index","level":3,"score":0.3610000014305115},{"id":"https://openalex.org/C130590232","wikidata":"https://www.wikidata.org/wiki/Q1671754","display_name":"Inverted index","level":3,"score":0.33390000462532043},{"id":"https://openalex.org/C161986146","wikidata":"https://www.wikidata.org/wiki/Q4896845","display_name":"Best bin first","level":3,"score":0.33090001344680786},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.3296000063419342},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3269999921321869},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.3244999945163727},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3109000027179718},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.27480000257492065},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C203689450","wikidata":"https://www.wikidata.org/wiki/Q2302053","display_name":"Spatial database","level":3,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3769843","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3769843","pdf_url":null,"source":{"id":"https://openalex.org/S4387289859","display_name":"Proceedings of the ACM on Management of Data","issn_l":"2836-6573","issn":["2836-6573"],"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 ACM on Management of Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8335078443","display_name":null,"funder_award_id":"2023ZD0503600/2023ZD0503604","funder_id":"https://openalex.org/F4320329860","funder_display_name":"National Science and Technology Major Project"}],"funders":[{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2026166434","https://openalex.org/W2077815765","https://openalex.org/W2086179657","https://openalex.org/W2086504823","https://openalex.org/W2124509324","https://openalex.org/W2204555070","https://openalex.org/W2949985202","https://openalex.org/W2963213486","https://openalex.org/W2963265099","https://openalex.org/W2963284996","https://openalex.org/W2963469388","https://openalex.org/W2998702515","https://openalex.org/W3005838368","https://openalex.org/W3085011441","https://openalex.org/W3136183693","https://openalex.org/W3164396702","https://openalex.org/W3196481040","https://openalex.org/W4226086155","https://openalex.org/W4312285477","https://openalex.org/W4366502978","https://openalex.org/W4384518989","https://openalex.org/W4393183654","https://openalex.org/W4399660853","https://openalex.org/W4399794670","https://openalex.org/W4400641571","https://openalex.org/W4404181049","https://openalex.org/W4405519454","https://openalex.org/W4407367173","https://openalex.org/W4407454670","https://openalex.org/W4409206472","https://openalex.org/W4410544010"],"related_works":[],"abstract_inverted_index":{"Given":[0],"a":[1,10,20,24,55,111],"hybrid":[2],"dataset":[3,42],"where":[4],"every":[5],"data":[6],"object":[7],"consists":[8],"of":[9,208],"vector":[11,22,59,152],"and":[12,23,43,63,95,151,179,204],"an":[13,77,121],"attribute":[14,46,148],"value,":[15],"for":[16,71,102,147,165],"each":[17],"query":[18,51,74,100],"with":[19,66,76,133,174,187],"target":[21],"range":[25,104,140,156],"filter,":[26],"range-filtering":[27],"approximate":[28],"nearest":[29,82],"neighbor":[30],"search":[31,146],"(RFANNS)":[32],"aims":[33],"to":[34,91,97,124],"retrieve":[35],"the":[36,41,44,50,89,168,175,183,199,206,209],"most":[37,176,184,200],"similar":[38],"vectors":[39],"from":[40],"corresponding":[45],"values":[47],"fall":[48],"in":[49,58],"range.":[52],"It":[53],"is":[54,171,195],"fundamental":[56],"function":[57],"database":[60],"management":[61],"systems":[62,65],"intelligent":[64],"embedding":[67],"abilities.":[68],"Dedicated":[69],"indices":[70],"RFANNS":[72,114,192],"accelerate":[73],"speed":[75],"acceptable":[78],"accuracy":[79],"loss":[80],"on":[81,160,172],"neighbors.":[83],"However,":[84],"they":[85],"are":[86],"still":[87],"facing":[88],"challenges":[90],"be":[92],"constructed":[93],"incrementally":[94],"generalized":[96],"achieve":[98],"superior":[99],"performance":[101,207],"arbitrary":[103,139],"filters.":[105],"In":[106],"this":[107],"paper,":[108],"we":[109,119,142],"introduce":[110],"window":[112,131,135,145],"graph-based":[113],"index.":[115,212],"For":[116,191],"incremental":[117,202],"construction,":[118,167],"propose":[120],"insertion":[122],"algorithm":[123],"add":[125],"new":[126],"vector-attribute":[127],"pairs":[128],"into":[129],"hierarchical":[130],"graphs":[132],"varying":[134],"size.":[136],"To":[137],"handle":[138],"filters,":[141],"optimize":[143],"relevant":[144],"filter":[149],"checks":[150],"distance":[153],"computations":[154],"by":[155],"selectivity.":[157],"Extensive":[158],"experiments":[159],"real-world":[161],"datasets":[162],"show":[163],"that":[164],"index":[166,186],"indexing":[169],"time":[170],"par":[173],"building-efficient":[177],"index,":[178,203],"4.9x":[180],"faster":[181,197],"than":[182,198],"query-efficient":[185],"0.4-0.5x":[188],"smaller":[189],"size;":[190],"query,":[193],"it":[194],"4x":[196],"efficient":[201],"matches":[205],"best":[210],"statically-built":[211]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-12-06T00:00:00"}