{"id":"https://openalex.org/W3128793550","doi":"https://doi.org/10.14778/3476249.3476255","title":"A comprehensive survey and experimental comparison of graph-based approximate nearest neighbor search","display_name":"A comprehensive survey and experimental comparison of graph-based approximate nearest neighbor search","publication_year":2021,"publication_date":"2021-07-01","ids":{"openalex":"https://openalex.org/W3128793550","doi":"https://doi.org/10.14778/3476249.3476255","mag":"3128793550"},"language":"en","primary_location":{"id":"doi:10.14778/3476249.3476255","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3476249.3476255","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":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2101.12631","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043365458","display_name":"Mengzhao Wang","orcid":"https://orcid.org/0000-0003-3806-1012"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengzhao Wang","raw_affiliation_strings":["Hangzhou Dianzi University, China","HangZhou Dianzi University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University, China","institution_ids":["https://openalex.org/I50760025"]},{"raw_affiliation_string":"HangZhou Dianzi University, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063412515","display_name":"Xiaoliang Xu","orcid":"https://orcid.org/0000-0001-8040-6809"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoliang Xu","raw_affiliation_strings":["Hangzhou Dianzi University, China","HangZhou Dianzi University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University, China","institution_ids":["https://openalex.org/I50760025"]},{"raw_affiliation_string":"HangZhou Dianzi University, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101581112","display_name":"Qiang Yue","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Yue","raw_affiliation_strings":["Hangzhou Dianzi University, China","HangZhou Dianzi University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University, China","institution_ids":["https://openalex.org/I50760025"]},{"raw_affiliation_string":"HangZhou Dianzi University, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100394398","display_name":"Yuxiang Wang","orcid":"https://orcid.org/0000-0003-3240-2912"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxiang Wang","raw_affiliation_strings":["Hangzhou Dianzi University, China","HangZhou Dianzi University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University, China","institution_ids":["https://openalex.org/I50760025"]},{"raw_affiliation_string":"HangZhou Dianzi University, China","institution_ids":["https://openalex.org/I50760025"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I50760025"],"apc_list":null,"apc_paid":null,"fwci":1.8194,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.85093253,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"14","issue":"11","first_page":"1964","last_page":"1978"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9994999766349792,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9764999747276306,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.7972791790962219},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.552963137626648},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5199279189109802},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5191178321838379},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.5097088813781738},{"id":"https://openalex.org/keywords/rule-of-thumb","display_name":"Rule of thumb","score":0.5037550330162048},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44443124532699585},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.42161113023757935},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.4209524393081665},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3649939298629761},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3467596769332886},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3259916603565216}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7972791790962219},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.552963137626648},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5199279189109802},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5191178321838379},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.5097088813781738},{"id":"https://openalex.org/C89246107","wikidata":"https://www.wikidata.org/wiki/Q1398821","display_name":"Rule of thumb","level":2,"score":0.5037550330162048},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44443124532699585},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.42161113023757935},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.4209524393081665},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3649939298629761},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3467596769332886},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3259916603565216},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.14778/3476249.3476255","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3476249.3476255","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"},{"id":"pmh:oai:arXiv.org:2101.12631","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2101.12631","pdf_url":"https://arxiv.org/pdf/2101.12631","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3128793550","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2101.12631","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2101.12631","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2101.12631","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":"pmh:oai:arXiv.org:2101.12631","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2101.12631","pdf_url":"https://arxiv.org/pdf/2101.12631","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":111,"referenced_works":["https://openalex.org/W17346433","https://openalex.org/W206566442","https://openalex.org/W299839057","https://openalex.org/W1541459201","https://openalex.org/W1542351876","https://openalex.org/W1550211845","https://openalex.org/W1603536826","https://openalex.org/W1965680834","https://openalex.org/W1967005434","https://openalex.org/W1978112828","https://openalex.org/W1980090536","https://openalex.org/W1986693891","https://openalex.org/W2001597875","https://openalex.org/W2003048487","https://openalex.org/W2007610503","https://openalex.org/W2023883913","https://openalex.org/W2033000863","https://openalex.org/W2038044292","https://openalex.org/W2042281163","https://openalex.org/W2042486644","https://openalex.org/W2043469923","https://openalex.org/W2044795021","https://openalex.org/W2058656956","https://openalex.org/W2063295648","https://openalex.org/W2084443125","https://openalex.org/W2086179657","https://openalex.org/W2099253838","https://openalex.org/W2101562895","https://openalex.org/W2105947278","https://openalex.org/W2110026675","https://openalex.org/W2111006384","https://openalex.org/W2112979232","https://openalex.org/W2114668036","https://openalex.org/W2121456571","https://openalex.org/W2122111042","https://openalex.org/W2124509324","https://openalex.org/W2126719278","https://openalex.org/W2128678576","https://openalex.org/W2130502756","https://openalex.org/W2144679084","https://openalex.org/W2149664435","https://openalex.org/W2163227453","https://openalex.org/W2228830251","https://openalex.org/W2250539671","https://openalex.org/W2291103301","https://openalex.org/W2291903501","https://openalex.org/W2294518132","https://openalex.org/W2411707397","https://openalex.org/W2427312773","https://openalex.org/W2427881153","https://openalex.org/W2511469006","https://openalex.org/W2523268797","https://openalex.org/W2526367648","https://openalex.org/W2537425075","https://openalex.org/W2729309190","https://openalex.org/W2757662681","https://openalex.org/W2772756366","https://openalex.org/W2795392346","https://openalex.org/W2796158081","https://openalex.org/W2797054769","https://openalex.org/W2799167061","https://openalex.org/W2838874902","https://openalex.org/W2890736686","https://openalex.org/W2891253335","https://openalex.org/W2895805257","https://openalex.org/W2901613577","https://openalex.org/W2907492528","https://openalex.org/W2946058642","https://openalex.org/W2947795536","https://openalex.org/W2948180465","https://openalex.org/W2950725338","https://openalex.org/W2960484119","https://openalex.org/W2962835968","https://openalex.org/W2963213486","https://openalex.org/W2963265099","https://openalex.org/W2963284996","https://openalex.org/W2964292992","https://openalex.org/W2966487933","https://openalex.org/W2967754694","https://openalex.org/W2969538544","https://openalex.org/W2970360209","https://openalex.org/W2972019369","https://openalex.org/W2972555443","https://openalex.org/W2977704877","https://openalex.org/W2984806015","https://openalex.org/W2986277806","https://openalex.org/W2991416621","https://openalex.org/W2994701319","https://openalex.org/W2996499210","https://openalex.org/W2998566393","https://openalex.org/W3004954215","https://openalex.org/W3005838368","https://openalex.org/W3006878628","https://openalex.org/W3008535402","https://openalex.org/W3010856967","https://openalex.org/W3011056378","https://openalex.org/W3028864969","https://openalex.org/W3029693508","https://openalex.org/W3032616711","https://openalex.org/W3037277842","https://openalex.org/W3084228038","https://openalex.org/W3085011441","https://openalex.org/W3096649713","https://openalex.org/W3103902563","https://openalex.org/W3105233790","https://openalex.org/W3127892494","https://openalex.org/W3136183693","https://openalex.org/W3173498609","https://openalex.org/W3196481040","https://openalex.org/W4210257598","https://openalex.org/W4292081294"],"related_works":["https://openalex.org/W2530877529","https://openalex.org/W2884112453","https://openalex.org/W1905709030","https://openalex.org/W96179457","https://openalex.org/W2584805731","https://openalex.org/W3092290393","https://openalex.org/W1971617833","https://openalex.org/W2066883679","https://openalex.org/W3150578066","https://openalex.org/W3118456734","https://openalex.org/W2927158114","https://openalex.org/W2239896693","https://openalex.org/W793359613","https://openalex.org/W3175869216","https://openalex.org/W3084125735","https://openalex.org/W3022922398","https://openalex.org/W3011417748","https://openalex.org/W3153624757","https://openalex.org/W2208446158","https://openalex.org/W1972143677"],"abstract_inverted_index":{"Approximate":[0],"nearest":[1,55],"neighbor":[2],"search":[3],"(ANNS)":[4],"constitutes":[5],"an":[6,151],"important":[7],"operation":[8],"in":[9,34,119,181],"a":[10,58,76,80,95,109,120],"multitude":[11],"of":[12,39,102],"applications,":[13],"including":[14],"recommendation":[15],"systems,":[16],"information":[17],"retrieval,":[18],"and":[19,67,89,99,112,128,135,176],"pattern":[20],"recognition.":[21],"In":[22],"the":[23,31,54,84,156],"past":[24],"decade,":[25],"graph-based":[26,40,105],"ANNS":[27,41,106],"algorithms":[28,42,45,69,107,178],"have":[29],"been":[30],"leading":[32],"paradigm":[33],"this":[35],"domain,":[36],"with":[37,70,132,169],"dozens":[38],"proposed.":[43],"Such":[44],"aim":[46],"to":[47,146],"provide":[48,94],"effective,":[49],"efficient":[50],"solutions":[51],"for":[52,57,79,179],"retrieving":[53],"neighbors":[56],"given":[59],"query.":[60],"Nevertheless,":[61],"these":[62],"efforts":[63],"focus":[64],"on":[65,124],"developing":[66],"optimizing":[68],"different":[71,182],"approaches,":[72],"so":[73],"there":[74],"is":[75],"real":[77],"need":[78],"comprehensive":[81],"survey":[82],"about":[83,172],"approaches'":[85],"relative":[86],"performance,":[87],"strengths,":[88],"pitfalls.":[90],"Thus":[91],"here":[92],"we":[93],"thorough":[96],"comparative":[97],"analysis":[98],"experimental":[100],"evaluation":[101],"13":[103],"representative":[104],"via":[108],"new":[110],"taxonomy":[111],"fine-grained":[113],"pipeline.":[114],"We":[115],"compared":[116],"each":[117],"algorithm":[118],"uniform":[121],"test":[122],"environment":[123],"eight":[125],"real-world":[126],"datasets":[127,131],"12":[129],"synthetic":[130],"varying":[133],"sizes":[134],"characteristics.":[136],"Our":[137],"study":[138],"yields":[139],"novel":[140],"discoveries,":[141],"offerings":[142],"several":[143],"useful":[144],"principles":[145],"improve":[147],"algorithms,":[148],"thus":[149],"designing":[150],"optimized":[152],"method":[153],"that":[154],"outperforms":[155],"state-of-the-art":[157],"algorithms.":[158],"This":[159],"effort":[160],"also":[161],"helped":[162],"us":[163],"pinpoint":[164],"algorithms'":[165],"working":[166],"portions,":[167],"along":[168],"rule-of-thumb":[170],"recommendations":[171],"promising":[173],"research":[174],"directions":[175],"suitable":[177],"practitioners":[180],"fields.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4}],"updated_date":"2026-07-01T08:55:40.977307","created_date":"2025-10-10T00:00:00"}
