{"id":"https://openalex.org/W3217092890","doi":"https://doi.org/10.14778/3476311.3476405","title":"Machine learning for databases","display_name":"Machine learning for databases","publication_year":2021,"publication_date":"2021-07-01","ids":{"openalex":"https://openalex.org/W3217092890","doi":"https://doi.org/10.14778/3476311.3476405","mag":"3217092890"},"language":"en","primary_location":{"id":"doi:10.14778/3476311.3476405","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3476311.3476405","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/A5100451576","display_name":"Guoliang Li","orcid":"https://orcid.org/0000-0002-1398-0621"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoliang Li","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056912386","display_name":"Xuanhe Zhou","orcid":"https://orcid.org/0000-0002-2285-7836"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuanhe Zhou","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049926126","display_name":"Lei Cao","orcid":"https://orcid.org/0000-0001-9909-8607"},"institutions":[{"id":"https://openalex.org/I4210109586","display_name":"Moscow Institute of Thermal Technology","ror":"https://ror.org/021es5e59","country_code":"RU","type":"facility","lineage":["https://openalex.org/I4210109586"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Lei Cao","raw_affiliation_strings":["MIT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MIT","institution_ids":["https://openalex.org/I4210109586"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.7429,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.94342114,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"14","issue":"12","first_page":"3190","last_page":"3193"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9980999827384949,"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":0.9980999827384949,"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":0.9943000078201294,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9934999942779541,"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":0.832720935344696},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6566335558891296},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.5601351857185364},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5438758134841919},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.447226881980896},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.38169458508491516}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.832720935344696},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6566335558891296},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.5601351857185364},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5438758134841919},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.447226881980896},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.38169458508491516},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14778/3476311.3476405","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3476311.3476405","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W2011318210","https://openalex.org/W2264196645","https://openalex.org/W2429298957","https://openalex.org/W2525739395","https://openalex.org/W2613206411","https://openalex.org/W2790625403","https://openalex.org/W2799015892","https://openalex.org/W2889503624","https://openalex.org/W2906910993","https://openalex.org/W2911464154","https://openalex.org/W2919531074","https://openalex.org/W2944240329","https://openalex.org/W2945486614","https://openalex.org/W2946655760","https://openalex.org/W2948513753","https://openalex.org/W2953896412","https://openalex.org/W2955798121","https://openalex.org/W2966185412","https://openalex.org/W2970148517","https://openalex.org/W2970545551","https://openalex.org/W2970851599","https://openalex.org/W2982236626","https://openalex.org/W2991530444","https://openalex.org/W2997325344","https://openalex.org/W2998249308","https://openalex.org/W3007086929","https://openalex.org/W3013555795","https://openalex.org/W3024784979","https://openalex.org/W3025775630","https://openalex.org/W3029327553","https://openalex.org/W3029535034","https://openalex.org/W3029564598","https://openalex.org/W3030387435","https://openalex.org/W3030994385","https://openalex.org/W3037027022","https://openalex.org/W3045448621","https://openalex.org/W3094011786","https://openalex.org/W3095166039","https://openalex.org/W3099158806","https://openalex.org/W3099273181","https://openalex.org/W3100077023","https://openalex.org/W3100925961","https://openalex.org/W3103567827","https://openalex.org/W3104631761","https://openalex.org/W3105457604","https://openalex.org/W3106489949","https://openalex.org/W3107270585","https://openalex.org/W3124277639","https://openalex.org/W3138077113","https://openalex.org/W3139827290","https://openalex.org/W3168288096","https://openalex.org/W3168955346","https://openalex.org/W3173622057","https://openalex.org/W3173850788","https://openalex.org/W3174465898","https://openalex.org/W3174969457","https://openalex.org/W3176434378","https://openalex.org/W3183953540","https://openalex.org/W3196849431","https://openalex.org/W3197917898","https://openalex.org/W6772169254"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3209574120","https://openalex.org/W3107602296","https://openalex.org/W4312192474","https://openalex.org/W4210805261","https://openalex.org/W4387297750"],"abstract_inverted_index":{"Machine":[0],"learning":[1,49,79,125],"techniques":[2,16,51,127],"have":[3],"been":[4],"proposed":[5],"to":[6,128],"optimize":[7],"the":[8,31,45],"databases.":[9],"For":[10],"example,":[11],"traditional":[12],"empirical":[13],"database":[14,36,66],"optimization":[15,59],"(e.g.,":[17,84,105,117],"cost":[18],"estimation,":[19,107,110],"join":[20,97],"order":[21,98],"selection,":[22,89],"knob":[23,85],"tuning,":[24],"index":[25],"and":[26,40,114,132],"view":[27],"advisor)":[28],"cannot":[29],"meet":[30],"high-performance":[32],"requirement":[33],"for":[34,92,100],"large-scale":[35],"instances,":[37],"various":[38],"applications":[39],"diversified":[41],"users,":[42],"especially":[43],"on":[44],"cloud.":[46],"Fortunately,":[47],"machine":[48,78,124],"based":[50,126],"can":[52,73],"alleviate":[53],"this":[54,62],"problem":[55],"by":[56,76],"judiciously":[57],"selecting":[58],"strategy.":[60],"In":[61],"tutorial,":[63],"we":[64],"categorize":[65],"tasks":[67],"into":[68],"three":[69],"typical":[70],"problems":[71,83,104,116,131],"that":[72],"be":[74],"optimized":[75],"different":[77],"models,":[80],"including":[81],"NP-hard":[82],"space":[86],"exploration,":[87],"index/view":[88,108],"partition-key":[90],"recommendation":[91],"offline":[93],"optimization;":[94],"query":[95,111,118],"rewrite,":[96],"selection":[99],"online":[101],"optimization),":[102],"regression":[103],"cost/cardinality":[106],"benefit":[109],"latency":[112],"prediction),":[113],"prediction":[115],"workload":[119],"prediction).":[120],"We":[121],"review":[122],"existing":[123],"address":[129],"these":[130],"provide":[133],"research":[134],"challenges.":[135]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":5}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
