{"id":"https://openalex.org/W7140086938","doi":"https://doi.org/10.1109/tkde.2026.3676465","title":"STABLE: Efficient Hybrid Nearest Neighbor Search via Magnitude-Uniformity and Cardinality-Robustness","display_name":"STABLE: Efficient Hybrid Nearest Neighbor Search via Magnitude-Uniformity and Cardinality-Robustness","publication_year":2026,"publication_date":"2026-03-23","ids":{"openalex":"https://openalex.org/W7140086938","doi":"https://doi.org/10.1109/tkde.2026.3676465"},"language":null,"primary_location":{"id":"doi:10.1109/tkde.2026.3676465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2026.3676465","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","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/A5130388821","display_name":"Qianyun Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qianyun Yang","raw_affiliation_strings":["School of Software, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0009-0002-5455-3113","affiliations":[{"raw_affiliation_string":"School of Software, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006118098","display_name":"Zhiwei Chen","orcid":"https://orcid.org/0000-0003-4724-278X"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwei Chen","raw_affiliation_strings":["School of Software, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0009-0003-0365-8553","affiliations":[{"raw_affiliation_string":"School of Software, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130372380","display_name":"Yupeng Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yupeng Hu","raw_affiliation_strings":["School of Software, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0002-5653-8286","affiliations":[{"raw_affiliation_string":"School of Software, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072617830","display_name":"Zhisheng Li","orcid":"https://orcid.org/0000-0001-7811-8285"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zixu Li","raw_affiliation_strings":["School of Software, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0009-0001-5136-159X","affiliations":[{"raw_affiliation_string":"School of Software, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130411236","display_name":"Zhiheng Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiheng Fu","raw_affiliation_strings":["School of Software, Shandong University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5130372058","display_name":"Liqiang Nie","orcid":null},"institutions":[{"id":"https://openalex.org/I158809036","display_name":"Shenzhen Institute of Information Technology","ror":"https://ror.org/03wrf9427","country_code":"CN","type":"education","lineage":["https://openalex.org/I158809036"]},{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liqiang Nie","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-1476-0273","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China","institution_ids":["https://openalex.org/I158809036","https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.38395438,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"38","issue":"6","first_page":"3927","last_page":"3944"},"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":0.1770000010728836,"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":0.1770000010728836,"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/T10057","display_name":"Face and Expression Recognition","score":0.07129999995231628,"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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.055799998342990875,"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/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.5153999924659729},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.5020999908447266},{"id":"https://openalex.org/keywords/best-bin-first","display_name":"Best bin first","score":0.3977000117301941},{"id":"https://openalex.org/keywords/algorithm-design","display_name":"Algorithm design","score":0.38609999418258667},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35409998893737793},{"id":"https://openalex.org/keywords/search-algorithm","display_name":"Search algorithm","score":0.302700012922287}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7483999729156494},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.5153999924659729},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.5020999908447266},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4036000072956085},{"id":"https://openalex.org/C161986146","wikidata":"https://www.wikidata.org/wiki/Q4896845","display_name":"Best bin first","level":3,"score":0.3977000117301941},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.38609999418258667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3573000133037567},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35409998893737793},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30300000309944153},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.302700012922287},{"id":"https://openalex.org/C53661774","wikidata":"https://www.wikidata.org/wiki/Q13108095","display_name":"Cover tree","level":5,"score":0.2987000048160553},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C3020028006","wikidata":"https://www.wikidata.org/wiki/Q9158","display_name":"Electronic mail","level":2,"score":0.2554999887943268},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2026.3676465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2026.3676465","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3981135610","display_name":null,"funder_award_id":"62276155","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7882649824","display_name":null,"funder_award_id":"62576195","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W4258001","https://openalex.org/W1994655805","https://openalex.org/W2063123441","https://openalex.org/W2077815765","https://openalex.org/W2079942837","https://openalex.org/W2086179657","https://openalex.org/W2086504823","https://openalex.org/W2090212574","https://openalex.org/W2099253838","https://openalex.org/W2110026675","https://openalex.org/W2124509324","https://openalex.org/W2133212952","https://openalex.org/W2153404040","https://openalex.org/W2171034893","https://openalex.org/W2204555070","https://openalex.org/W2228830251","https://openalex.org/W2266931272","https://openalex.org/W2294518132","https://openalex.org/W2328694828","https://openalex.org/W2343414189","https://openalex.org/W2343796173","https://openalex.org/W2345395130","https://openalex.org/W2427312773","https://openalex.org/W2441967103","https://openalex.org/W2606197134","https://openalex.org/W2616739377","https://openalex.org/W2772923331","https://openalex.org/W2797054769","https://openalex.org/W2892816441","https://openalex.org/W2895810692","https://openalex.org/W2901613577","https://openalex.org/W2940946889","https://openalex.org/W2949985202","https://openalex.org/W2963265099","https://openalex.org/W2963284996","https://openalex.org/W2963469388","https://openalex.org/W2991342176","https://openalex.org/W3004561114","https://openalex.org/W3029079605","https://openalex.org/W3037277842","https://openalex.org/W3084228038","https://openalex.org/W3085011441","https://openalex.org/W3085456122","https://openalex.org/W3092103025","https://openalex.org/W3136183693","https://openalex.org/W3157181916","https://openalex.org/W3174809957","https://openalex.org/W3196481040","https://openalex.org/W4306317701","https://openalex.org/W4362465355","https://openalex.org/W4367046898","https://openalex.org/W4379792729","https://openalex.org/W4381329135","https://openalex.org/W4381610063","https://openalex.org/W4384523577","https://openalex.org/W4385653226","https://openalex.org/W4399174383","https://openalex.org/W4405623265","https://openalex.org/W4414243411"],"related_works":[],"abstract_inverted_index":{"Hybrid":[0],"Approximate":[1],"Nearest":[2],"Neighbor":[3],"Search":[4],"(Hybrid":[5],"ANNS)":[6],"is":[7],"a":[8,93,136],"foundational":[9],"search":[10],"technology":[11],"for":[12,43,69],"large-scale":[13],"heterogeneous":[14,130],"data":[15,33],"and":[16,24,47,72,99,106],"has":[17],"gained":[18],"significant":[19],"attention":[20],"in":[21,32],"both":[22],"academia":[23],"industry.":[25],"However,":[26],"current":[27],"approaches":[28],"overlook":[29],"the":[30,40,48,60,159],"heterogeneity":[31,105],"distribution,":[34],"thus":[35],"ignoring":[36],"two":[37],"major":[38],"challenges:":[39],"Compatibility":[41],"Barrier":[42],"Similarity":[44],"Magnitude":[45],"Heterogeneity":[46,139],"Tolerance":[49],"Bottleneck":[50],"to":[51,91,109,128,142],"Attribute":[52],"Cardinality.":[53],"To":[54],"overcome":[55],"these":[56],"issues,":[57],"we":[58,82,116,134],"propose":[59],"robuSt":[61],"he":[62],"Terogeneity-Aware":[63],"hyBrid":[64],"retrievaL":[65],"framEwork,":[66],"STABLE,":[67],"designed":[68],"accurate,":[70],"efficient,":[71],"robust":[73],"hybrid":[74],"ANNS":[75],"under":[76],"datasets":[77,110],"with":[78,111,154],"various":[79,112,155],"distributions.":[80],"Specifically,":[81],"introduce":[83],"an":[84,144],"enhAnced":[85],"heterogeneoUs":[86],"semanTic":[87],"perceptiOn":[88],"(AUTO)":[89],"metric":[90],"achieve":[92],"joint":[94],"measurement":[95],"of":[96,162],"feature":[97,151],"similarity":[98,103],"attribute":[100,113,156],"consistency,":[101],"addressing":[102],"magnitude":[104],"improving":[107],"robustness":[108],"cardinalities.":[114],"Thereafter,":[115],"construct":[117],"our":[118],"Heterogeneous":[119],"Emanticre":[120],"Lation":[121],"graPh":[122],"(HELP)":[123],"index":[124],"based":[125],"on":[126,149],"AUTO":[127],"organize":[129],"semantic":[131],"relations.":[132],"Finally,":[133],"employ":[135],"novel":[137],"Dynamic":[138],"Routing":[140],"method":[141],"ensure":[143],"efficient":[145],"search.":[146],"Extensive":[147],"experiments":[148],"five":[150],"vector":[152],"benchmarks":[153],"cardinalities":[157],"demonstrate":[158],"superior":[160],"performance":[161],"STABLE.":[163]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-24T00:00:00"}
