{"id":"https://openalex.org/W2609979645","doi":"https://doi.org/10.1145/3078971.3078992","title":"Accelerated Nearest Neighbor Search with Quick ADC","display_name":"Accelerated Nearest Neighbor Search with Quick ADC","publication_year":2017,"publication_date":"2017-05-25","ids":{"openalex":"https://openalex.org/W2609979645","doi":"https://doi.org/10.1145/3078971.3078992","mag":"2609979645"},"language":"en","primary_location":{"id":"doi:10.1145/3078971.3078992","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3078971.3078992","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1704.07355","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Fabien Andr\u00e9","orcid":null},"institutions":[{"id":"https://openalex.org/I4210121266","display_name":"Technicolor (France)","ror":"https://ror.org/02ya5n776","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210121266"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Fabien Andr\u00e9","raw_affiliation_strings":["Technicolor, Rennes, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technicolor, Rennes, France","institution_ids":["https://openalex.org/I4210121266"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Anne-Marie Kermarrec","orcid":null},"institutions":[{"id":"https://openalex.org/I4210133778","display_name":"Inria Rennes - Bretagne Atlantique Research Centre","ror":"https://ror.org/04040yw90","country_code":"FR","type":"government","lineage":["https://openalex.org/I1326498283","https://openalex.org/I4210133778"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Anne-Marie Kermarrec","raw_affiliation_strings":["Inria, Rennes, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inria, Rennes, France","institution_ids":["https://openalex.org/I4210133778"]}]},{"author_position":"last","author":{"id":null,"display_name":"Nicolas Le Scouarnec","orcid":null},"institutions":[{"id":"https://openalex.org/I4210121266","display_name":"Technicolor (France)","ror":"https://ror.org/02ya5n776","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210121266"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Nicolas Le Scouarnec","raw_affiliation_strings":["Technicolor, Rennes, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technicolor, Rennes, France","institution_ids":["https://openalex.org/I4210121266"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210121266"],"apc_list":null,"apc_paid":null,"fwci":0.6468,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.78028907,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"159","last_page":"166"},"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":0.9998999834060669,"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":0.9998999834060669,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9961000084877014,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.6552000045776367},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.6409000158309937},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6001999974250793},{"id":"https://openalex.org/keywords/lookup-table","display_name":"Lookup table","score":0.5277000069618225},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5249000191688538},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.5241000056266785},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48159998655319214},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.4577000141143799},{"id":"https://openalex.org/keywords/cache","display_name":"Cache","score":0.4187999963760376}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7247999906539917},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.6552000045776367},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.6409000158309937},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6001999974250793},{"id":"https://openalex.org/C134835016","wikidata":"https://www.wikidata.org/wiki/Q690265","display_name":"Lookup table","level":2,"score":0.5277000069618225},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5249000191688538},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.5241000056266785},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48159998655319214},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.4577000141143799},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45100000500679016},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.4187999963760376},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40880000591278076},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.40799999237060547},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3894999921321869},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.36090001463890076},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.3564000129699707},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3522000014781952},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33649998903274536},{"id":"https://openalex.org/C161986146","wikidata":"https://www.wikidata.org/wiki/Q4896845","display_name":"Best bin first","level":3,"score":0.33180001378059387},{"id":"https://openalex.org/C102164700","wikidata":"https://www.wikidata.org/wiki/Q17162702","display_name":"Nearest-neighbor chain algorithm","level":5,"score":0.3285999894142151},{"id":"https://openalex.org/C53661774","wikidata":"https://www.wikidata.org/wiki/Q13108095","display_name":"Cover tree","level":5,"score":0.32850000262260437},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32089999318122864},{"id":"https://openalex.org/C184879717","wikidata":"https://www.wikidata.org/wiki/Q1374523","display_name":"Nearest neighbour algorithm","level":3,"score":0.3003000020980835},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27639999985694885},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.27079999446868896},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C3018263672","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Efficient algorithm","level":2,"score":0.267300009727478}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3078971.3078992","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3078971.3078992","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1704.07355","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1704.07355","pdf_url":"https://arxiv.org/pdf/1704.07355","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":"pmh:oai:HAL:hal-01660730v1","is_oa":false,"landing_page_url":"https://inria.hal.science/hal-01660730","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ICMR 2017 - ACM International Conference on Multimedia Retrieval, Jun 2017, Bucarest, Romania. pp.159-166, ⟨10.1145/3078971.3078992⟩","raw_type":"Conference papers"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1704.07355","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1704.07355","pdf_url":"https://arxiv.org/pdf/1704.07355","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":14,"referenced_works":["https://openalex.org/W1566135517","https://openalex.org/W1911745671","https://openalex.org/W1974048680","https://openalex.org/W1977182282","https://openalex.org/W1980090536","https://openalex.org/W2038752770","https://openalex.org/W2073299621","https://openalex.org/W2076439560","https://openalex.org/W2077815765","https://openalex.org/W2124386111","https://openalex.org/W2124509324","https://openalex.org/W2132234208","https://openalex.org/W2148554573","https://openalex.org/W2204555070"],"related_works":[],"abstract_inverted_index":{"Efficient":[0],"Nearest":[1],"Neighbor":[2],"(NN)":[3],"search":[4],"in":[5],"high-dimensional":[6,31,74],"spaces":[7],"is":[8,25,64],"a":[9,26],"foundation":[10],"of":[11,43,62,82],"many":[12,95],"multimedia":[13],"retrieval":[14],"systems.":[15],"Because":[16],"it":[17,66,93],"offers":[18],"low":[19],"responses":[20],"times,":[21],"Product":[22],"Quantization":[23],"(PQ)":[24],"popular":[27],"solution.":[28],"PQ":[29,63],"compresses":[30],"vectors":[32,75],"into":[33],"short":[34,71],"codes":[35,72],"using":[36,76],"several":[37],"sub-quantizers,":[38],"which":[39],"enables":[40],"in-RAM":[41],"storage":[42],"large":[44],"databases.":[45],"This":[46],"allows":[47],"fast":[48],"answers":[49],"to":[50],"NN":[51],"queries,":[52],"without":[53],"accessing":[54],"the":[55],"SSD":[56],"or":[57],"HDD.":[58],"The":[59,80],"key":[60],"feature":[61],"that":[65],"can":[67],"compute":[68],"distances":[69],"between":[70],"and":[73],"cache-resident":[77],"lookup":[78],"tables.":[79],"efficiency":[81],"this":[83],"technique,":[84],"named":[85],"Asymmetric":[86],"Distance":[87],"Computation":[88],"(ADC),":[89],"remains":[90],"limited":[91],"because":[92],"performs":[94],"cache":[96],"accesses.":[97]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-05-07T13:39:58.223016","created_date":"2017-05-05T00:00:00"}