{"id":"https://openalex.org/W2112842248","doi":"https://doi.org/10.14778/2536360.2536368","title":"Making queries tractable on big data with preprocessing","display_name":"Making queries tractable on big data with preprocessing","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W2112842248","doi":"https://doi.org/10.14778/2536360.2536368","mag":"2112842248"},"language":"en","primary_location":{"id":"doi:10.14778/2536360.2536368","is_oa":false,"landing_page_url":"https://doi.org/10.14778/2536360.2536368","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":"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/A5070565287","display_name":"Wenfei Fan","orcid":"https://orcid.org/0000-0001-5149-2656"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]},{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["CN","GB"],"is_corresponding":true,"raw_author_name":"Wenfei Fan","raw_affiliation_strings":["Informatics, University of Edinburgh & RCBD and SKLSDE Lab, Beihang University","Informatics, University of Edinburgh & RCBD and SKLSDE Lab, Beihang University#TAB#"],"affiliations":[{"raw_affiliation_string":"Informatics, University of Edinburgh & RCBD and SKLSDE Lab, Beihang University","institution_ids":["https://openalex.org/I82880672","https://openalex.org/I98677209"]},{"raw_affiliation_string":"Informatics, University of Edinburgh & RCBD and SKLSDE Lab, Beihang University#TAB#","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087587379","display_name":"Floris Geerts","orcid":"https://orcid.org/0000-0002-8967-2473"},"institutions":[{"id":"https://openalex.org/I149213910","display_name":"University of Antwerp","ror":"https://ror.org/008x57b05","country_code":"BE","type":"education","lineage":["https://openalex.org/I149213910"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Floris Geerts","raw_affiliation_strings":["University of Antwerp","UNIVERSITY OF ANTWERP*"],"affiliations":[{"raw_affiliation_string":"University of Antwerp","institution_ids":["https://openalex.org/I149213910"]},{"raw_affiliation_string":"UNIVERSITY OF ANTWERP*","institution_ids":["https://openalex.org/I149213910"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022264843","display_name":"Frank Neven","orcid":"https://orcid.org/0000-0002-7143-1903"},"institutions":[{"id":"https://openalex.org/I878454856","display_name":"Hasselt University","ror":"https://ror.org/04nbhqj75","country_code":"BE","type":"education","lineage":["https://openalex.org/I878454856"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Frank Neven","raw_affiliation_strings":["Hasselt University & transnational University of Limburg"],"affiliations":[{"raw_affiliation_string":"Hasselt University & transnational University of Limburg","institution_ids":["https://openalex.org/I878454856"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5070565287"],"corresponding_institution_ids":["https://openalex.org/I82880672","https://openalex.org/I98677209"],"apc_list":null,"apc_paid":null,"fwci":4.5001,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.95053044,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"6","issue":"9","first_page":"685","last_page":"696"},"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9995999932289124,"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":0.9980999827384949,"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/p","display_name":"P","score":0.9470469951629639},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.702885091304779},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5260367393493652},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.51581209897995},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4687359929084778},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.45756015181541443},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4436027705669403},{"id":"https://openalex.org/keywords/time-complexity","display_name":"Time complexity","score":0.4408940076828003},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4390116035938263},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22846871614456177},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.19013962149620056},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.10162815451622009},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08930703997612}],"concepts":[{"id":"https://openalex.org/C134026603","wikidata":"https://www.wikidata.org/wiki/Q846354","display_name":"P","level":3,"score":0.9470469951629639},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.702885091304779},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5260367393493652},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.51581209897995},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4687359929084778},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.45756015181541443},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4436027705669403},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.4408940076828003},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4390116035938263},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22846871614456177},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.19013962149620056},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.10162815451622009},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08930703997612},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.14778/2536360.2536368","is_oa":false,"landing_page_url":"https://doi.org/10.14778/2536360.2536368","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:documentserver.uhasselt.be:1942/15806","is_oa":false,"landing_page_url":"http://hdl.handle.net/1942/15806","pdf_url":null,"source":{"id":"https://openalex.org/S4306401926","display_name":"Document Server@UHasselt (UHasselt)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I878454856","host_organization_name":"Hasselt University","host_organization_lineage":["https://openalex.org/I878454856"],"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":"info:eu-repo/semantics/article"},{"id":"pmh:oai:pure.ed.ac.uk:publications/e87b1ecc-20e1-4e52-a194-bc8b3eb6ee45","is_oa":false,"landing_page_url":"https://www.research.ed.ac.uk/portal/en/publications/making-queries-tractable-on-big-data-with-preprocessing(e87b1ecc-20e1-4e52-a194-bc8b3eb6ee45).html","pdf_url":null,"source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W36639738","https://openalex.org/W1497287285","https://openalex.org/W1506378440","https://openalex.org/W1558832481","https://openalex.org/W1558964774","https://openalex.org/W1570425181","https://openalex.org/W1854661526","https://openalex.org/W1963838724","https://openalex.org/W1966205523","https://openalex.org/W1972978715","https://openalex.org/W1992673035","https://openalex.org/W2007791040","https://openalex.org/W2011039300","https://openalex.org/W2012797687","https://openalex.org/W2022357808","https://openalex.org/W2023062809","https://openalex.org/W2029852131","https://openalex.org/W2033258621","https://openalex.org/W2045271686","https://openalex.org/W2049354208","https://openalex.org/W2051586153","https://openalex.org/W2064757275","https://openalex.org/W2075620950","https://openalex.org/W2077436409","https://openalex.org/W2082773934","https://openalex.org/W2085393535","https://openalex.org/W2091434162","https://openalex.org/W2094908973","https://openalex.org/W2097745829","https://openalex.org/W2100132188","https://openalex.org/W2106355650","https://openalex.org/W2108781142","https://openalex.org/W2132750992","https://openalex.org/W2138556324","https://openalex.org/W2142491343","https://openalex.org/W2152191782","https://openalex.org/W2163087774","https://openalex.org/W2165971212","https://openalex.org/W2173213060","https://openalex.org/W2476096155","https://openalex.org/W2666600683","https://openalex.org/W2753710282","https://openalex.org/W2949093975","https://openalex.org/W3157585079","https://openalex.org/W4206031975","https://openalex.org/W4213009134","https://openalex.org/W4241342151","https://openalex.org/W4300928490","https://openalex.org/W6630400633","https://openalex.org/W6633513001","https://openalex.org/W6633989784","https://openalex.org/W6638822256","https://openalex.org/W6657794752","https://openalex.org/W6658632641","https://openalex.org/W6663617415","https://openalex.org/W6665909358","https://openalex.org/W6669360320","https://openalex.org/W6675208004","https://openalex.org/W6676373393","https://openalex.org/W6679722788","https://openalex.org/W6680501568","https://openalex.org/W6683791690","https://openalex.org/W6990023262","https://openalex.org/W7018146823"],"related_works":["https://openalex.org/W1577561363","https://openalex.org/W2148283143","https://openalex.org/W1541916735","https://openalex.org/W4390608645","https://openalex.org/W2890950593","https://openalex.org/W1886510939","https://openalex.org/W1519444547","https://openalex.org/W1828234149","https://openalex.org/W4289670448","https://openalex.org/W2889033124"],"abstract_inverted_index":{"A":[0,32],"query":[1,113,132,167,218],"class":[2,51,168],"is":[3,41,169,199,229],"traditionally":[4],"considered":[5],"tractable":[6],"if":[7],"there":[8],"exists":[9],"a":[10,65,79,127,152,165,230],"polynomial-time":[11],"(PTIME)":[12],"algorithm":[13],"to":[14,21,37,42,63,90,139,157],"answer":[15],"its":[16,144],"queries.":[17,209],"When":[18],"it":[19],"comes":[20],"big":[22,121,242],"data,":[23],"however,":[24],"PTIME":[25,105,208,217],"algorithms":[26],"often":[27],"become":[28],"infeasible":[29],"in":[30,49,71,99,202,238],"practice.":[31],"traditional":[33],"and":[34,117,146],"effective":[35],"approach":[36,70],"coping":[38],"with":[39],"this":[40,69],"preprocess":[43],"data":[44,58,145],"off-line,":[45],"so":[46],"that":[47,95,110,134,164,179],"queries":[48,94,141,147,198,237],"the":[50,57,190,203,234,239],"can":[52,96,135,220],"be":[53,97,136,221],"subsequently":[54],"evaluated":[55],"on":[56,120],"efficiently.":[59],"This":[60,227],"paper":[61],"aims":[62],"provide":[64],"formal":[66],"foundation":[67],"for":[68,148,171],"terms":[72],"of":[73,81,93,131,154,195,206,236,241],"computational":[74],"complexity.":[75],"(1)":[76],"We":[77,108,124,150,162,176],"propose":[78],"set":[80,128,191,204],"\u03a0-tractable":[82,116,140,197,223],"queries,":[83],"denoted":[84],"by":[85,142],"\u03a0T":[86,129,172,180,192,211],"Q":[87,130,173,181,193,212],"0":[88,182,194],",":[89],"characterize":[91,158],"classes":[92,114,133,219],"answered":[98],"parallel":[100],"poly-logarithmic":[101],"time":[102],"(NC)":[103],"after":[104],"preprocessing.":[106,149],"(2)":[107],"show":[109,163,178],"several":[111],"natural":[112,166],"are":[115,118],"feasible":[119],"data.":[122,243],"(3)":[123],"also":[125,177],"study":[126],"effectively":[137],"converted":[138],"refactorizing":[143],"introduce":[151],"form":[153],"NC":[155],"reductions":[156],"such":[159],"conversions.":[160],"(4)":[161],"complete":[170],".":[174],"(5)":[175],"\u2282":[183],"P":[184,186,205],"unless":[185],"=":[187,213],"NC,":[188],"i.e.,":[189,215],"all":[196,207,216],"properly":[200],"contained":[201],"Nonetheless,":[210],"P,":[214],"made":[222],"via":[224],"proper":[225],"refactorizations.":[226],"work":[228],"step":[231],"towards":[232],"understanding":[233],"tractability":[235],"context":[240]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":7},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}