{"id":"https://openalex.org/W1511011071","doi":"https://doi.org/10.1109/icde.2015.7113340","title":"Optimizing recursive queries with monotonic aggregates in DeALS","display_name":"Optimizing recursive queries with monotonic aggregates in DeALS","publication_year":2015,"publication_date":"2015-04-01","ids":{"openalex":"https://openalex.org/W1511011071","doi":"https://doi.org/10.1109/icde.2015.7113340","mag":"1511011071"},"language":"en","primary_location":{"id":"doi:10.1109/icde.2015.7113340","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2015.7113340","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 31st International Conference on Data Engineering","raw_type":"proceedings-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/A5073720497","display_name":"Alexander Shkapsky","orcid":null},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Alexander Shkapsky","raw_affiliation_strings":["University of California, Los Angeles","University of California\u2013Los Angeles USA"],"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles","institution_ids":["https://openalex.org/I161318765"]},{"raw_affiliation_string":"University of California\u2013Los Angeles USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103075868","display_name":"Mohan Yang","orcid":"https://orcid.org/0000-0002-6886-0256"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohan Yang","raw_affiliation_strings":["University of California, Los Angeles","University of California\u2013Los Angeles USA"],"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles","institution_ids":["https://openalex.org/I161318765"]},{"raw_affiliation_string":"University of California\u2013Los Angeles USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113467760","display_name":"Carlo Zaniolo","orcid":null},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carlo Zaniolo","raw_affiliation_strings":["University of California, Los Angeles","University of California\u2013Los Angeles USA"],"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles","institution_ids":["https://openalex.org/I161318765"]},{"raw_affiliation_string":"University of California\u2013Los Angeles USA","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5073720497"],"corresponding_institution_ids":["https://openalex.org/I161318765"],"apc_list":null,"apc_paid":null,"fwci":5.6579,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.9614633,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"867","last_page":"878"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9991999864578247,"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/T11010","display_name":"Logic, Reasoning, and Knowledge","score":0.9979000091552734,"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"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9939000010490417,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/generality","display_name":"Generality","score":0.9321959614753723},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8014758825302124},{"id":"https://openalex.org/keywords/datalog","display_name":"Datalog","score":0.754848837852478},{"id":"https://openalex.org/keywords/recursion","display_name":"Recursion (computer science)","score":0.7363913059234619},{"id":"https://openalex.org/keywords/syntax","display_name":"Syntax","score":0.6517305374145508},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.6288291215896606},{"id":"https://openalex.org/keywords/deductive-database","display_name":"Deductive database","score":0.49692490696907043},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.46676725149154663},{"id":"https://openalex.org/keywords/monotonic-function","display_name":"Monotonic function","score":0.4576919972896576},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.44423651695251465},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4435620605945587},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.43869712948799133},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.41977012157440186},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2435695230960846},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.2121131420135498}],"concepts":[{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.9321959614753723},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8014758825302124},{"id":"https://openalex.org/C148230440","wikidata":"https://www.wikidata.org/wiki/Q1172264","display_name":"Datalog","level":2,"score":0.754848837852478},{"id":"https://openalex.org/C168773036","wikidata":"https://www.wikidata.org/wiki/Q264164","display_name":"Recursion (computer science)","level":2,"score":0.7363913059234619},{"id":"https://openalex.org/C60048249","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntax","level":2,"score":0.6517305374145508},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.6288291215896606},{"id":"https://openalex.org/C2777502361","wikidata":"https://www.wikidata.org/wiki/Q1182254","display_name":"Deductive database","level":2,"score":0.49692490696907043},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.46676725149154663},{"id":"https://openalex.org/C72169020","wikidata":"https://www.wikidata.org/wiki/Q194404","display_name":"Monotonic function","level":2,"score":0.4576919972896576},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.44423651695251465},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4435620605945587},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.43869712948799133},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.41977012157440186},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2435695230960846},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2121131420135498},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icde.2015.7113340","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2015.7113340","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 31st International Conference on Data Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W102682372","https://openalex.org/W166666332","https://openalex.org/W193566757","https://openalex.org/W1486392831","https://openalex.org/W1502641483","https://openalex.org/W1507455930","https://openalex.org/W1524668325","https://openalex.org/W1590360882","https://openalex.org/W1664357009","https://openalex.org/W1768000531","https://openalex.org/W1846087057","https://openalex.org/W2012670464","https://openalex.org/W2016531106","https://openalex.org/W2035298354","https://openalex.org/W2046413390","https://openalex.org/W2056116767","https://openalex.org/W2063545044","https://openalex.org/W2064864283","https://openalex.org/W2065975085","https://openalex.org/W2094818741","https://openalex.org/W2096650850","https://openalex.org/W2098678491","https://openalex.org/W2101310065","https://openalex.org/W2105905502","https://openalex.org/W2106355650","https://openalex.org/W2106500031","https://openalex.org/W2145067417","https://openalex.org/W2155996966","https://openalex.org/W2156536027","https://openalex.org/W2167108874","https://openalex.org/W2167845698","https://openalex.org/W2170719314","https://openalex.org/W2339351027","https://openalex.org/W2953245771","https://openalex.org/W4230201548","https://openalex.org/W4236806770","https://openalex.org/W4296313421","https://openalex.org/W6604173785","https://openalex.org/W6607884761","https://openalex.org/W6631393269","https://openalex.org/W6639055759","https://openalex.org/W6664740515","https://openalex.org/W6674971812","https://openalex.org/W6764818655"],"related_works":["https://openalex.org/W1565767456","https://openalex.org/W4242285398","https://openalex.org/W2593015871","https://openalex.org/W1582387176","https://openalex.org/W4245106022","https://openalex.org/W2583213513","https://openalex.org/W1945902811","https://openalex.org/W2058395701","https://openalex.org/W2079714382","https://openalex.org/W2948754138"],"abstract_inverted_index":{"The":[0,92,196],"exploding":[1],"demand":[2],"for":[3,24,83],"analytics":[4],"has":[5],"refocused":[6],"the":[7,20,44,66,90,115,161,165],"attention":[8],"of":[9,22,46,59,94,98,119,141],"data":[10,41],"scientists":[11],"on":[12,193],"applications":[13,142],"requiring":[14],"aggregation":[15],"in":[16,89,101,150],"recursion.":[17],"After":[18],"resisting":[19],"efforts":[21],"researchers":[23],"more":[25],"than":[26],"twenty":[27],"years,":[28],"this":[29],"problem":[30],"is":[31],"being":[32],"addressed":[33],"by":[34,106],"innovative":[35],"systems":[36,192],"that":[37,50,110,112,175],"are":[38,51,87],"raising":[39],"logic-oriented":[40],"languages":[42],"to":[43,53,136,164],"levels":[45],"generality":[47,74,207],"and":[48,75,80,132,168,172],"performance":[49,76,166],"needed":[52],"support":[54],"efficiently":[55],"a":[56,95,138],"broad":[57],"range":[58],"applications.":[60],"Foremost":[61],"among":[62],"these":[63],"new":[64,78],"systems,":[65,202],"Deductive":[67],"Application":[68],"Language":[69],"System":[70],"(DeALS)":[71],"achieves":[72],"superior":[73,206,209],"via":[77],"constructs":[79],"optimization":[81,173],"techniques":[82,174],"monotonic":[84,99],"aggregates":[85,100],"which":[86],"described":[88],"paper.":[91],"use":[93],"special":[96],"class":[97],"recursion":[102],"was":[103,186],"made":[104],"possible":[105],"recent":[107],"theoretical":[108],"results":[109,197],"proved":[111],"they":[113],"preserve":[114],"rigorous":[116],"least-fixpoint":[117],"semantics":[118],"core":[120],"Datalog":[121],"programs.":[122],"This":[123],"paper":[124,162],"thus":[125],"describes":[126],"how":[127],"DeALS":[128,189,203],"extends":[129],"their":[130,134],"definitions":[131],"modifies":[133],"syntax":[135],"enable":[137],"concise":[139],"expression":[140],"that,":[143,199],"without":[144],"them,":[145],"could":[146,154],"not":[147,155],"be":[148,156],"expressed":[149,157],"performance-conducive":[151],"ways,":[152],"or":[153],"at":[158],"all.":[159],"Then":[160],"turns":[163],"issue,":[167],"introduces":[169],"novel":[170],"implementation":[171],"outperform":[176],"traditional":[177],"approaches,":[178],"including":[179],"Semi-naive":[180],"evaluation.":[181],"An":[182],"extensive":[183],"experimental":[184],"evaluation":[185],"executed":[187],"comparing":[188],"with":[190,208],"other":[191,201],"large":[194],"datasets.":[195],"suggest":[198],"unlike":[200],"indeed":[204],"combines":[205],"performance.":[210]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}