{"id":"https://openalex.org/W2905128908","doi":"https://doi.org/10.1109/bigdata.2018.8621943","title":"Revisiting Exact kNN Query Processing with Probabilistic Data Space Transformations","display_name":"Revisiting Exact kNN Query Processing with Probabilistic Data Space Transformations","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2905128908","doi":"https://doi.org/10.1109/bigdata.2018.8621943","mag":"2905128908"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2018.8621943","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8621943","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069400576","display_name":"Atoshum Cahsai","orcid":null},"institutions":[{"id":"https://openalex.org/I7882870","display_name":"University of Glasgow","ror":"https://ror.org/00vtgdb53","country_code":"GB","type":"education","lineage":["https://openalex.org/I7882870"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Atoshum Cahsai","raw_affiliation_strings":["School of Computing Science, University of Glasgow, UK"],"affiliations":[{"raw_affiliation_string":"School of Computing Science, University of Glasgow, UK","institution_ids":["https://openalex.org/I7882870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001331936","display_name":"Christos Anagnostopoulos","orcid":"https://orcid.org/0000-0003-1517-6757"},"institutions":[{"id":"https://openalex.org/I7882870","display_name":"University of Glasgow","ror":"https://ror.org/00vtgdb53","country_code":"GB","type":"education","lineage":["https://openalex.org/I7882870"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Christos Anagnostopoulos","raw_affiliation_strings":["School of Computing Science, University of Glasgow, UK"],"affiliations":[{"raw_affiliation_string":"School of Computing Science, University of Glasgow, UK","institution_ids":["https://openalex.org/I7882870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021697915","display_name":"Nikos Ntarmos","orcid":"https://orcid.org/0000-0001-8676-0948"},"institutions":[{"id":"https://openalex.org/I7882870","display_name":"University of Glasgow","ror":"https://ror.org/00vtgdb53","country_code":"GB","type":"education","lineage":["https://openalex.org/I7882870"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Nikos Ntarmos","raw_affiliation_strings":["School of Computing Science, University of Glasgow, UK"],"affiliations":[{"raw_affiliation_string":"School of Computing Science, University of Glasgow, UK","institution_ids":["https://openalex.org/I7882870"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052475427","display_name":"Peter Triantafillou","orcid":"https://orcid.org/0000-0002-5807-6011"},"institutions":[{"id":"https://openalex.org/I39555362","display_name":"University of Warwick","ror":"https://ror.org/01a77tt86","country_code":"GB","type":"education","lineage":["https://openalex.org/I39555362"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Peter Triantafillou","raw_affiliation_strings":["Department of Computer Science, University of Warwick, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Warwick, UK","institution_ids":["https://openalex.org/I39555362"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5069400576"],"corresponding_institution_ids":["https://openalex.org/I7882870"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15746341,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":null,"first_page":"653","last_page":"662"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":1.0,"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":1.0,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9983000159263611,"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"}},{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9977999925613403,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8016625642776489},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7868484258651733},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.7378479242324829},{"id":"https://openalex.org/keywords/nosql","display_name":"NoSQL","score":0.6338649988174438},{"id":"https://openalex.org/keywords/memory-footprint","display_name":"Memory footprint","score":0.5718462467193604},{"id":"https://openalex.org/keywords/spark","display_name":"SPARK (programming language)","score":0.5616386532783508},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5512816905975342},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5462205410003662},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.489719420671463},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.47142237424850464},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.45607712864875793},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.45115506649017334},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.4407202899456024},{"id":"https://openalex.org/keywords/petabyte","display_name":"Petabyte","score":0.4216262698173523},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.41825804114341736},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.3292931318283081},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.25571465492248535},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2061379849910736}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8016625642776489},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7868484258651733},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.7378479242324829},{"id":"https://openalex.org/C2779599972","wikidata":"https://www.wikidata.org/wiki/Q82231","display_name":"NoSQL","level":3,"score":0.6338649988174438},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.5718462467193604},{"id":"https://openalex.org/C2781215313","wikidata":"https://www.wikidata.org/wiki/Q3493345","display_name":"SPARK (programming language)","level":2,"score":0.5616386532783508},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5512816905975342},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5462205410003662},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.489719420671463},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.47142237424850464},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.45607712864875793},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.45115506649017334},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.4407202899456024},{"id":"https://openalex.org/C13600138","wikidata":"https://www.wikidata.org/wiki/Q8799","display_name":"Petabyte","level":3,"score":0.4216262698173523},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.41825804114341736},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.3292931318283081},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.25571465492248535},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2061379849910736},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/bigdata.2018.8621943","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8621943","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.gla.ac.uk:171798","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4210235606","display_name":"ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam)","issn_l":"2622-8912","issn":["2622-8912","2622-8920"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceedings"},{"id":"pmh:oai:eprints.gla.ac.uk:172710","is_oa":true,"landing_page_url":"http://eprints.gla.ac.uk/view/author/39215.html>,","pdf_url":null,"source":{"id":"https://openalex.org/S4210235606","display_name":"ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam)","issn_l":"2622-8912","issn":["2622-8912","2622-8920"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"}],"best_oa_location":{"id":"pmh:oai:eprints.gla.ac.uk:171798","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4210235606","display_name":"ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam)","issn_l":"2622-8912","issn":["2622-8912","2622-8920"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceedings"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1505133516","https://openalex.org/W1854079585","https://openalex.org/W1980486587","https://openalex.org/W1992402718","https://openalex.org/W2000053898","https://openalex.org/W2008196645","https://openalex.org/W2011316986","https://openalex.org/W2016130389","https://openalex.org/W2038412523","https://openalex.org/W2046144220","https://openalex.org/W2049633694","https://openalex.org/W2051278494","https://openalex.org/W2053166411","https://openalex.org/W2060195349","https://openalex.org/W2063922845","https://openalex.org/W2071188048","https://openalex.org/W2098280243","https://openalex.org/W2098994245","https://openalex.org/W2115583184","https://openalex.org/W2118269922","https://openalex.org/W2135961964","https://openalex.org/W2146651522","https://openalex.org/W2148817137","https://openalex.org/W2157355837","https://openalex.org/W2165558283","https://openalex.org/W2168175751","https://openalex.org/W2189465200","https://openalex.org/W2197411628","https://openalex.org/W2205234449","https://openalex.org/W2295338537","https://openalex.org/W2311161367","https://openalex.org/W2436533802","https://openalex.org/W2548613432","https://openalex.org/W2734480475","https://openalex.org/W2752313434","https://openalex.org/W2766616325","https://openalex.org/W2802533528","https://openalex.org/W2907233437","https://openalex.org/W2962894282","https://openalex.org/W2963213486","https://openalex.org/W3003570628","https://openalex.org/W3120740533","https://openalex.org/W4244933504","https://openalex.org/W6681928353","https://openalex.org/W6687322159"],"related_works":["https://openalex.org/W1538652242","https://openalex.org/W2011521129","https://openalex.org/W2461968736","https://openalex.org/W4379164835","https://openalex.org/W2031298432","https://openalex.org/W4386544342","https://openalex.org/W2799973158","https://openalex.org/W2888933188","https://openalex.org/W2186366292","https://openalex.org/W4388843294"],"abstract_inverted_index":{"The":[0,75,165],"state-of-the-art":[1,189],"approaches":[2],"for":[3,32,93],"scalable":[4],"kNN":[5],"query":[6,34,99,174,181],"processing":[7,100,175,182],"utilise":[8],"big":[9],"data":[10,38,81,95],"parallel/distributed":[11],"platforms":[12],"(e.g.,":[13],"Hadoop":[14],"and":[15,17,85,198,206],"Spark)":[16],"storage":[18,53],"engines":[19],"(e.g,":[20],"HDFS,":[21],"NoSQL,":[22],"etc.),":[23],"upon":[24],"which":[25],"they":[26],"build":[27],"(tree":[28],"based)":[29],"indexing":[30],"methods":[31],"efficient":[33,157],"processing.":[35],"However,":[36],"as":[37,101],"sizes":[39,203],"continue":[40],"to":[41,48,70,158,187,204],"increase":[42],"(nowadays":[43],"it":[44],"is":[45,121,155],"not":[46],"uncommon":[47],"reach":[49],"several":[50],"Petabytes),":[51],"the":[52,133,152,188,208],"cost":[54],"of":[55,124,201,211],"tree-based":[56],"index":[57,162],"structures":[58],"becomes":[59],"exceptionally":[60],"high.":[61],"In":[62],"this":[63],"work,":[64,138],"we":[65],"propose":[66],"a":[67,87,116,171],"novel":[68,77],"perspective":[69],"organise":[71],"multivariate":[72],"(mv)":[73],"datasets.":[74],"main":[76],"idea":[78],"relies":[79],"on":[80],"space":[82],"probabilistic":[83],"transformations":[84],"derives":[86],"Space":[88],"Transformation":[89],"Organisation":[90],"Structure":[91],"(STOS)":[92],"mv":[94],"organisation.":[96],"STOS":[97,114,153],"facilitates":[98],"if":[102],"underlying":[103],"datasets":[104,200],"were":[105],"uniformly":[106],"distributed.":[107],"This":[108],"approach":[109,167],"bears":[110],"significant":[111],"advantages.":[112],"First,":[113],"enjoys":[115,147],"minute":[117],"memory":[118],"footprint":[119],"that":[120],"many":[122],"orders":[123],"magnitude":[125],"smaller":[126],"than":[127],"indexes":[128],"in":[129],"related":[130,137],"work.":[131],"Second,":[132],"required":[134],"memory,":[135],"unlike":[136],"increases":[139],"very":[140],"slowly":[141],"with":[142,170,196],"dataset":[143],"size":[144],"and,":[145],"thus,":[146],"significantly":[148],"higher":[149],"scalability.":[150],"Third,":[151],"structure":[154],"relatively":[156],"compute,":[159],"outperforming":[160],"traditional":[161],"building":[163],"times.":[164],"new":[166],"comes":[168],"bundled":[169],"distributed":[172],"coordinator-based":[173],"method":[176],"so":[177],"that,":[178],"overall,":[179],"lower":[180],"times":[183],"are":[184],"achieved":[185],"compared":[186],"index-based":[190],"methods.":[191],"We":[192],"conducted":[193],"extensive":[194],"experimentation":[195],"real":[197],"synthetic":[199],"different":[202],"substantiate":[205],"quantify":[207],"performance":[209],"advantages":[210],"our":[212],"proposal.":[213]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
