{"id":"https://openalex.org/W7136185965","doi":"https://doi.org/10.48550/arxiv.2603.12913","title":"RNSG: A Range-Aware Graph Index for Efficient Range-Filtered Approximate Nearest Neighbor Search","display_name":"RNSG: A Range-Aware Graph Index for Efficient Range-Filtered Approximate Nearest Neighbor Search","publication_year":2026,"publication_date":"2026-03-13","ids":{"openalex":"https://openalex.org/W7136185965","doi":"https://doi.org/10.48550/arxiv.2603.12913"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.12913","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12913","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.12913","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024601387","display_name":"Zhiqiu Zou","orcid":"https://orcid.org/0000-0003-0229-0171"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zou, Zhiqiu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129557390","display_name":"Ziqi Yin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yin, Ziqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129424718","display_name":"Rong-Hua Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Rong-Hua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059652667","display_name":"Hongchao Qin","orcid":"https://orcid.org/0000-0003-4364-0633"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qin, Hongchao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030519392","display_name":"Qiangqiang Dai","orcid":"https://orcid.org/0000-0002-8569-6558"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dai, Qiangqiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129409900","display_name":"Guoren Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Guoren","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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":0.31369999051094055,"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":0.31369999051094055,"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":0.1736000031232834,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.1096000000834465,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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":0.7452999949455261},{"id":"https://openalex.org/keywords/nearest-neighbor-graph","display_name":"Nearest neighbor graph","score":0.6191999912261963},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5117999911308289},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.49799999594688416},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.4771000146865845},{"id":"https://openalex.org/keywords/monotonic-function","display_name":"Monotonic function","score":0.3824999928474426},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.376800000667572},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.32339999079704285},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.3140999972820282},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.3084999918937683}],"concepts":[{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.7452999949455261},{"id":"https://openalex.org/C90988772","wikidata":"https://www.wikidata.org/wiki/Q2855103","display_name":"Nearest neighbor graph","level":3,"score":0.6191999912261963},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5489000082015991},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5117999911308289},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.49799999594688416},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.4771000146865845},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4194999933242798},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3880000114440918},{"id":"https://openalex.org/C72169020","wikidata":"https://www.wikidata.org/wiki/Q194404","display_name":"Monotonic function","level":2,"score":0.3824999928474426},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.376800000667572},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37610000371932983},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32600000500679016},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.32339999079704285},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.3140999972820282},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.3084999918937683},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.30489999055862427},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C136736807","wikidata":"https://www.wikidata.org/wiki/Q818943","display_name":"Range query (database)","level":5,"score":0.2978000044822693},{"id":"https://openalex.org/C128115575","wikidata":"https://www.wikidata.org/wiki/Q5597083","display_name":"Graph factorization","level":5,"score":0.2833999991416931},{"id":"https://openalex.org/C203689450","wikidata":"https://www.wikidata.org/wiki/Q2302053","display_name":"Spatial database","level":3,"score":0.27889999747276306},{"id":"https://openalex.org/C176225458","wikidata":"https://www.wikidata.org/wiki/Q595971","display_name":"Graph database","level":3,"score":0.2782000005245209},{"id":"https://openalex.org/C59276292","wikidata":"https://www.wikidata.org/wiki/Q580427","display_name":"Database index","level":3,"score":0.2777999937534332},{"id":"https://openalex.org/C3018263672","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Efficient algorithm","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C94475309","wikidata":"https://www.wikidata.org/wiki/Q6489154","display_name":"Large margin nearest neighbor","level":3,"score":0.2680000066757202},{"id":"https://openalex.org/C64339825","wikidata":"https://www.wikidata.org/wiki/Q722659","display_name":"Graph property","level":5,"score":0.2651999890804291},{"id":"https://openalex.org/C161986146","wikidata":"https://www.wikidata.org/wiki/Q4896845","display_name":"Best bin first","level":3,"score":0.26190000772476196},{"id":"https://openalex.org/C19332903","wikidata":"https://www.wikidata.org/wiki/Q7623247","display_name":"Strength of a graph","level":5,"score":0.2583000063896179},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C122818955","wikidata":"https://www.wikidata.org/wiki/Q1060343","display_name":"Independent set","level":3,"score":0.25699999928474426},{"id":"https://openalex.org/C3018596841","wikidata":"https://www.wikidata.org/wiki/Q7236523","display_name":"Power index","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C53661774","wikidata":"https://www.wikidata.org/wiki/Q13108095","display_name":"Cover tree","level":5,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.12913","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12913","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.12913","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12913","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6211815476417542}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Range-filtered":[0],"approximate":[1],"nearest":[2,32,114],"neighbor":[3,115],"(RFANN)":[4],"search":[5,57,137],"is":[6],"a":[7,15,21,24,35,81,131,139,150,157,195],"fundamental":[8],"operation":[9],"in":[10],"modern":[11],"data":[12],"systems.":[13],"Given":[14],"set":[16],"of":[17],"objects,":[18],"each":[19],"with":[20,138,178,194],"vector":[22,37],"and":[23,96,120,174,199],"numerical":[25,42],"attribute,":[26],"an":[27],"RFANN":[28,56,176],"query":[29,36,68,192],"retrieves":[30],"the":[31,46,50,86,102,171],"neighbors":[33],"to":[34,65],"among":[38],"those":[39],"objects":[40],"whose":[41],"attributes":[43],"fall":[44],"within":[45],"range":[47],"specified":[48],"by":[49],"query.":[51],"Existing":[52],"state-of-the-art":[53,205],"methods":[54],"for":[55,168],"often":[58],"require":[59],"constructing":[60,170],"multiple":[61],"range-specific":[62],"graph":[63,83,90,141,152],"indexes":[64],"achieve":[66],"high":[67],"performance,":[69],"which":[70,92,111,124],"incurs":[71],"significant":[72],"indexing":[73,84],"overhead.":[74],"To":[75],"address":[76],"this,":[77],"we":[78,148],"first":[79],"establish":[80],"novel":[82],"theory,":[85],"range-aware":[87],"relative":[88],"neighborhood":[89],"(RRNG),":[91],"jointly":[93],"considers":[94],"spatial":[95],"attribute":[97],"proximity.":[98],"We":[99,164],"prove":[100],"that":[101,126,160,187],"RRNG":[103],"satisfies":[104],"two":[105],"crucial":[106],"properties:":[107],"(1)":[108],"monotonic":[109],"search-ability,":[110],"ensures":[112],"correct":[113],"retrieval":[116],"via":[117],"beam":[118],"search;":[119],"(2)":[121],"structural":[122],"heredity,":[123],"guarantees":[125],"any":[127],"range-induced":[128],"subgraph":[129],"remains":[130],"valid":[132],"RRNG,":[133],"thus":[134],"enabling":[135],"efficient":[136],"single":[140],"index.":[142],"Based":[143],"on":[144,182],"this":[145],"theoretical":[146],"foundation,":[147],"propose":[149],"new":[151],"index":[153,173,198],"called":[154],"RNSG":[155,172,188],"as":[156],"practical":[158],"solution":[159],"efficiently":[161],"approximates":[162],"RRNG.":[163],"develop":[165],"fast":[166],"algorithms":[167],"both":[169],"processing":[175],"queries":[177],"it.":[179],"Extensive":[180],"experiments":[181],"five":[183],"real-world":[184],"datasets":[185],"show":[186],"achieves":[189],"significantly":[190],"higher":[191],"performance":[193],"more":[196],"compact":[197],"lower":[200],"construction":[201],"cost":[202],"than":[203],"existing":[204],"methods.":[206]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-17T00:00:00"}
