{"id":"https://openalex.org/W2537932269","doi":"https://doi.org/10.1109/etfa.2014.7005188","title":"Fast classification in industrial Big Data environments","display_name":"Fast classification in industrial Big Data environments","publication_year":2014,"publication_date":"2014-09-01","ids":{"openalex":"https://openalex.org/W2537932269","doi":"https://doi.org/10.1109/etfa.2014.7005188","mag":"2537932269"},"language":"en","primary_location":{"id":"doi:10.1109/etfa.2014.7005188","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa.2014.7005188","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5036334927","display_name":"Helene D\u00f6rksen","orcid":null},"institutions":[{"id":"https://openalex.org/I5209920","display_name":"Ostwestfalen-Lippe University of Applied Sciences and Arts","ror":"https://ror.org/04eka8j06","country_code":"DE","type":"education","lineage":["https://openalex.org/I5209920"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Helene Dorksen","raw_affiliation_strings":["inIT \u2013 Institute Industrial IT, Ostwestfalen-Lippe University of Applied Sciences, Lemgo, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"inIT \u2013 Institute Industrial IT, Ostwestfalen-Lippe University of Applied Sciences, Lemgo, Germany","institution_ids":["https://openalex.org/I5209920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056365501","display_name":"Uwe M\u00f6nks","orcid":"https://orcid.org/0000-0003-1015-0697"},"institutions":[{"id":"https://openalex.org/I5209920","display_name":"Ostwestfalen-Lippe University of Applied Sciences and Arts","ror":"https://ror.org/04eka8j06","country_code":"DE","type":"education","lineage":["https://openalex.org/I5209920"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Uwe Monks","raw_affiliation_strings":["inIT \u2013 Institute Industrial IT, Ostwestfalen-Lippe University of Applied Sciences, Lemgo, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"inIT \u2013 Institute Industrial IT, Ostwestfalen-Lippe University of Applied Sciences, Lemgo, Germany","institution_ids":["https://openalex.org/I5209920"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003230577","display_name":"Volker Lohweg","orcid":"https://orcid.org/0000-0002-3325-7887"},"institutions":[{"id":"https://openalex.org/I5209920","display_name":"Ostwestfalen-Lippe University of Applied Sciences and Arts","ror":"https://ror.org/04eka8j06","country_code":"DE","type":"education","lineage":["https://openalex.org/I5209920"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Volker Lohweg","raw_affiliation_strings":["inIT \u2013 Institute Industrial IT, Ostwestfalen-Lippe University of Applied Sciences, Lemgo, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"inIT \u2013 Institute Industrial IT, Ostwestfalen-Lippe University of Applied Sciences, Lemgo, Germany","institution_ids":["https://openalex.org/I5209920"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I5209920"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"45","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9977999925613403,"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"}},"topics":[{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9977999925613403,"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/T10320","display_name":"Neural Networks and Applications","score":0.9958999752998352,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9925000071525574,"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/big-data","display_name":"Big data","score":0.7806665897369385},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7370188236236572},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5714856386184692},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5572851300239563},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5156170725822449},{"id":"https://openalex.org/keywords/realisation","display_name":"Realisation","score":0.4760946035385132},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4679231643676758},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44476449489593506},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42650026082992554},{"id":"https://openalex.org/keywords/actuator","display_name":"Actuator","score":0.4116450250148773}],"concepts":[{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.7806665897369385},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7370188236236572},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5714856386184692},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5572851300239563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5156170725822449},{"id":"https://openalex.org/C2779462738","wikidata":"https://www.wikidata.org/wiki/Q17146409","display_name":"Realisation","level":2,"score":0.4760946035385132},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4679231643676758},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44476449489593506},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42650026082992554},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.4116450250148773},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/etfa.2014.7005188","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa.2014.7005188","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W53188351","https://openalex.org/W1560724230","https://openalex.org/W1604585277","https://openalex.org/W1663973292","https://openalex.org/W1966501577","https://openalex.org/W1974387440","https://openalex.org/W1983989471","https://openalex.org/W2013373704","https://openalex.org/W2033918639","https://openalex.org/W2037142028","https://openalex.org/W2041775009","https://openalex.org/W2087347434","https://openalex.org/W2109722477","https://openalex.org/W2109773197","https://openalex.org/W2137583987","https://openalex.org/W2142997497","https://openalex.org/W2164463086","https://openalex.org/W2167277498","https://openalex.org/W2173213060","https://openalex.org/W2480645619","https://openalex.org/W2540488895","https://openalex.org/W2547440996","https://openalex.org/W2797148637","https://openalex.org/W3035630051","https://openalex.org/W3120740533","https://openalex.org/W4206070770","https://openalex.org/W4230492855","https://openalex.org/W4301347335","https://openalex.org/W6629510986","https://openalex.org/W6636174462","https://openalex.org/W6779330718","https://openalex.org/W7033523746"],"related_works":["https://openalex.org/W2961288924","https://openalex.org/W2075250579","https://openalex.org/W2789329261","https://openalex.org/W3016281454","https://openalex.org/W2538215832","https://openalex.org/W2810895613","https://openalex.org/W2187980447","https://openalex.org/W2567712142","https://openalex.org/W1725894279","https://openalex.org/W2188989229"],"abstract_inverted_index":{"Many":[0],"modern":[1],"industrial":[2,128,153],"applications,":[3],"e.g.":[4],"those":[5],"incorporating":[6],"hundreds":[7],"or":[8],"thousands":[9],"of":[10,55,66,142],"electrical":[11],"sensors":[12],"and":[13,41,73,149],"actuators,":[14],"must":[15,42],"be":[16,43],"categorised":[17],"into":[18],"Big":[19,129],"Data":[20,130],"environments,":[21],"in":[22,36,46,87,107,111,121],"which":[23,69,91],"it":[24],"is":[25,39,62,70,92],"essential":[26],"to":[27,99,114,132],"design":[28,65],"suitable":[29],"information":[30],"processing":[31,35],"models.":[32],"Central":[33],"data":[34,147],"such":[37],"environments":[38],"impossible":[40],"carried":[44],"out":[45],"a":[47,67,151],"distributed":[48],"way":[49],"on":[50,94,144,150],"resource-limited":[51],"cyber-physical":[52],"systems.":[53],"One":[54],"the":[56,64,115,139],"challenging":[57],"tasks":[58],"for":[59,83,119],"machine":[60],"learning":[61],"thus":[63],"classifier":[68],"simple,":[71],"accurate":[72],"has":[74],"an":[75],"acceptable":[76],"realisation":[77],"time.":[78],"We":[79],"present":[80],"ComRef-2D-ConvHull":[81,143],"method":[82],"linear":[84],"classification":[85,105],"optimisation":[86,106],"lower-dimensional":[88],"feature":[89,109,123],"space,":[90,124],"based":[93],"ComRef":[95],"from":[96,134],"[1].":[97],"Compared":[98],"original":[100],"ComRef,":[101],"we":[102,125],"consider":[103],"only":[104],"2-dimensional":[108,122],"spaces":[110],"ComRef-2D-ConvHull.":[112],"Due":[113],"decreased":[116],"time":[117],"complexity":[118],"calculations":[120],"expect":[126],"many":[127],"enviroments":[131],"profit":[133],"our":[135],"method.":[136],"Tests":[137],"regarding":[138],"generalisation":[140],"ability":[141],"several":[145],"reference":[146],"sets":[148],"real-world":[152],"dataset":[154],"show":[155],"promising":[156],"results.":[157]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
