{"id":"https://openalex.org/W2904194741","doi":"https://doi.org/10.1007/s41060-018-0163-5","title":"Large-scale predictive modeling and analytics through regression queries in data management systems","display_name":"Large-scale predictive modeling and analytics through regression queries in data management systems","publication_year":2018,"publication_date":"2018-12-27","ids":{"openalex":"https://openalex.org/W2904194741","doi":"https://doi.org/10.1007/s41060-018-0163-5","mag":"2904194741"},"language":"en","primary_location":{"id":"doi:10.1007/s41060-018-0163-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41060-018-0163-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41060-018-0163-5.pdf","source":{"id":"https://openalex.org/S4210195017","display_name":"International Journal of Data Science and Analytics","issn_l":"2364-415X","issn":["2364-415X","2364-4168"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319972","host_organization_name":"Springer International Publishing","host_organization_lineage":["https://openalex.org/P4310319972","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer International Publishing","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Science and Analytics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s41060-018-0163-5.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001331936","display_name":"Christos Anagnostopoulos","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":"Christos Anagnostopoulos","raw_affiliation_strings":["School of Computing Science, University of Glasgow, Glasgow, G12 8QQ, UK"],"affiliations":[{"raw_affiliation_string":"School of Computing Science, University of Glasgow, Glasgow, G12 8QQ, 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, Coventry, CV4 7AL, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK","institution_ids":["https://openalex.org/I39555362"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5001331936"],"corresponding_institution_ids":["https://openalex.org/I7882870"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.3316,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.59110417,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"9","issue":"1","first_page":"17","last_page":"55"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9987000226974487,"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":0.9987000226974487,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9947999715805054,"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/predictive-analytics","display_name":"Predictive analytics","score":0.6539880633354187},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6501660346984863},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5940674543380737},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.5817215442657471},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5502809882164001},{"id":"https://openalex.org/keywords/piecewise","display_name":"Piecewise","score":0.54796302318573},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5252016186714172},{"id":"https://openalex.org/keywords/data-analysis","display_name":"Data analysis","score":0.4849443733692169},{"id":"https://openalex.org/keywords/segmented-regression","display_name":"Segmented regression","score":0.4780505299568176},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4646807014942169},{"id":"https://openalex.org/keywords/exploratory-data-analysis","display_name":"Exploratory data analysis","score":0.4439624845981598},{"id":"https://openalex.org/keywords/proper-linear-model","display_name":"Proper linear model","score":0.41600337624549866},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3417905867099762},{"id":"https://openalex.org/keywords/polynomial-regression","display_name":"Polynomial regression","score":0.22422629594802856},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2129945158958435},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.13812139630317688}],"concepts":[{"id":"https://openalex.org/C83209312","wikidata":"https://www.wikidata.org/wiki/Q1053367","display_name":"Predictive analytics","level":2,"score":0.6539880633354187},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6501660346984863},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5940674543380737},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.5817215442657471},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5502809882164001},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.54796302318573},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5252016186714172},{"id":"https://openalex.org/C175801342","wikidata":"https://www.wikidata.org/wiki/Q1988917","display_name":"Data analysis","level":2,"score":0.4849443733692169},{"id":"https://openalex.org/C35519122","wikidata":"https://www.wikidata.org/wiki/Q3775699","display_name":"Segmented regression","level":4,"score":0.4780505299568176},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4646807014942169},{"id":"https://openalex.org/C120894424","wikidata":"https://www.wikidata.org/wiki/Q1322871","display_name":"Exploratory data analysis","level":2,"score":0.4439624845981598},{"id":"https://openalex.org/C32224588","wikidata":"https://www.wikidata.org/wiki/Q7250175","display_name":"Proper linear model","level":4,"score":0.41600337624549866},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3417905867099762},{"id":"https://openalex.org/C120068334","wikidata":"https://www.wikidata.org/wiki/Q45343","display_name":"Polynomial regression","level":3,"score":0.22422629594802856},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2129945158958435},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.13812139630317688},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s41060-018-0163-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41060-018-0163-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41060-018-0163-5.pdf","source":{"id":"https://openalex.org/S4210195017","display_name":"International Journal of Data Science and Analytics","issn_l":"2364-415X","issn":["2364-415X","2364-4168"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319972","host_organization_name":"Springer International Publishing","host_organization_lineage":["https://openalex.org/P4310319972","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer International Publishing","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Science and Analytics","raw_type":"journal-article"},{"id":"pmh:oai:eprints.gla.ac.uk:175039","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":"Articles"}],"best_oa_location":{"id":"doi:10.1007/s41060-018-0163-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41060-018-0163-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41060-018-0163-5.pdf","source":{"id":"https://openalex.org/S4210195017","display_name":"International Journal of Data Science and Analytics","issn_l":"2364-415X","issn":["2364-415X","2364-4168"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319972","host_organization_name":"Springer International Publishing","host_organization_lineage":["https://openalex.org/P4310319972","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer International Publishing","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Science and Analytics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1989121949","display_name":null,"funder_award_id":"EP/R018634/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G484905167","display_name":null,"funder_award_id":"GNFUV Project RAWFIE\u2013OC2\u2013EXP\u2013SCI Grant#645220","funder_id":"https://openalex.org/F4320337669","funder_display_name":"H2020 European Institute of Innovation and Technology"},{"id":"https://openalex.org/G7331901853","display_name":null,"funder_award_id":"EU H2020","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"}],"funders":[{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"},{"id":"https://openalex.org/F4320337669","display_name":"H2020 European Institute of Innovation and Technology","ror":"https://ror.org/036dxts37"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2904194741.pdf","grobid_xml":"https://content.openalex.org/works/W2904194741.grobid-xml"},"referenced_works_count":64,"referenced_works":["https://openalex.org/W791281155","https://openalex.org/W1480376833","https://openalex.org/W1489537150","https://openalex.org/W1491711721","https://openalex.org/W1591966886","https://openalex.org/W1597926580","https://openalex.org/W1669551046","https://openalex.org/W1782277269","https://openalex.org/W1922598422","https://openalex.org/W1955857676","https://openalex.org/W1970369278","https://openalex.org/W1971585680","https://openalex.org/W1989017925","https://openalex.org/W2020516950","https://openalex.org/W2026258334","https://openalex.org/W2029538739","https://openalex.org/W2032607604","https://openalex.org/W2033559660","https://openalex.org/W2039111092","https://openalex.org/W2039434802","https://openalex.org/W2061521613","https://openalex.org/W2068484625","https://openalex.org/W2082083863","https://openalex.org/W2082990111","https://openalex.org/W2088005382","https://openalex.org/W2090850279","https://openalex.org/W2092644566","https://openalex.org/W2098749003","https://openalex.org/W2101341561","https://openalex.org/W2101593450","https://openalex.org/W2105641627","https://openalex.org/W2110902297","https://openalex.org/W2113651538","https://openalex.org/W2116832440","https://openalex.org/W2131140847","https://openalex.org/W2144354472","https://openalex.org/W2146635036","https://openalex.org/W2151744781","https://openalex.org/W2168967034","https://openalex.org/W2284514301","https://openalex.org/W2294117933","https://openalex.org/W2309679942","https://openalex.org/W2470983053","https://openalex.org/W2530314904","https://openalex.org/W2550072831","https://openalex.org/W2564406132","https://openalex.org/W2565148050","https://openalex.org/W2585502432","https://openalex.org/W2598177319","https://openalex.org/W2606494425","https://openalex.org/W2742443763","https://openalex.org/W2767598234","https://openalex.org/W2769253851","https://openalex.org/W2792384079","https://openalex.org/W2808198108","https://openalex.org/W2990138404","https://openalex.org/W3083161613","https://openalex.org/W3100886003","https://openalex.org/W3103695676","https://openalex.org/W3105099198","https://openalex.org/W3105458558","https://openalex.org/W3105806700","https://openalex.org/W4229602251","https://openalex.org/W4238284510"],"related_works":["https://openalex.org/W1564729776","https://openalex.org/W2042934214","https://openalex.org/W623416330","https://openalex.org/W2991792261","https://openalex.org/W2910278425","https://openalex.org/W4247358537","https://openalex.org/W1972371432","https://openalex.org/W1496469336","https://openalex.org/W4376644189","https://openalex.org/W600390644"],"abstract_inverted_index":{"Regression":[0],"analytics":[1,24,38,65,200],"has":[2],"been":[3],"the":[4,9,109,118,129,155,166,172,189],"standard":[5],"approach":[6],"to":[7,20,36,50,95,111,124,146,171],"modeling":[8],"relationship":[10],"between":[11,122],"input":[12],"and":[13,39,57,67,77,91,105,116,127,140,180,185],"output":[14],"variables,":[15],"while":[16],"recent":[17],"trends":[18],"aim":[19],"incorporate":[21],"advanced":[22],"regression":[23,32,89,104,125],"capabilities":[25],"within":[26,133],"data":[27,130,135,141,151,157],"management":[28],"systems":[29],"(DMS).":[30],"Linear":[31],"queries":[33,90,126],"are":[34,74],"fundamental":[35],"exploratory":[37],"predictive":[40,64],"modeling.":[41],"However,":[42],"computing":[43],"their":[44,92],"exact":[45,183],"answers":[46,93,110],"leaves":[47],"a":[48,62,96,148],"lot":[49],"be":[51],"desired":[52],"in":[53,79,107,199],"terms":[54],"of":[55,188,196],"efficiency":[56],"scalability.":[58],"We":[59,98],"contribute":[60],"with":[61,165,182],"novel":[63],"model":[66],"an":[68],"associated":[69],"statistical":[70],"learning":[71],"methodology,":[72],"which":[73],"efficient,":[75],"scalable":[76],"accurate":[78],"discovering":[80],"piecewise":[81,102,119,149,168],"linear":[82,103,120,150,169],"dependencies":[83,121],"among":[84,192],"variables":[85,123,132,193],"by":[86,138],"observing":[87],"only":[88,158],"issued":[94],"DMS.":[97],"focus":[99],"on":[100],"in-DMS":[101],"specifically":[106],"predicting":[108,128],"mean-value":[112],"aggregate":[113],"queries,":[114],"identifying":[115],"delivering":[117],"dependent":[131],"specific":[134],"subspaces":[136],"defined":[137],"analysts":[139],"scientists.":[142],"Our":[143,175],"goal":[144],"is":[145,163,177],"discover":[147],"function":[152],"approximation":[153,170],"over":[154],"underlying":[156,190],"through":[159],"query\u2013answer":[160],"pairs":[161],"that":[162],"competitive":[164],"best":[167],"ground":[173],"truth.":[174],"methodology":[176],"analyzed,":[178],"evaluated":[179],"compared":[181],"solution":[184],"near-perfect":[186],"approximations":[187],"relationships":[191],"achieving":[194],"orders":[195],"magnitude":[197],"improvement":[198],"processing.":[201]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}