乐胖代购免代理版

{"id":"https://openalex.org/W2783605012","doi":"https://doi.org/10.1109/bigdata.2017.8258008","title":"A distributed rough set theory based algorithm for an efficient big data pre-processing under the spark framework","display_name":"A distributed rough set theory based algorithm for an efficient big data pre-processing under the spark framework","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2783605012","doi":"https://doi.org/10.1109/bigdata.2017.8258008","mag":"2783605012"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258008","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://research.aber.ac.uk/files/26109236/IEEEBigData2017_acceptedVersion.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018448962","display_name":"Zaineb Chelly Dagdia","orcid":"https://orcid.org/0000-0002-2551-6586"},"institutions":[{"id":"https://openalex.org/I16038530","display_name":"Aberystwyth University","ror":"https://ror.org/015m2p889","country_code":"GB","type":"education","lineage":["https://openalex.org/I16038530"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zaineb Chelly Dagdia","raw_affiliation_strings":["Department of Computer Science, Aberystywth University, Aberystwyth, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Aberystywth University, Aberystwyth, United Kingdom","institution_ids":["https://openalex.org/I16038530"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083499604","display_name":"Christine Zarges","orcid":"https://orcid.org/0000-0002-2829-4296"},"institutions":[{"id":"https://openalex.org/I16038530","display_name":"Aberystwyth University","ror":"https://ror.org/015m2p889","country_code":"GB","type":"education","lineage":["https://openalex.org/I16038530"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Christine Zarges","raw_affiliation_strings":["Department of Computer Science, Aberystywth University, Aberystwyth, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Aberystywth University, Aberystwyth, United Kingdom","institution_ids":["https://openalex.org/I16038530"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001516070","display_name":"Ga\u00ebl Beck","orcid":"https://orcid.org/0000-0002-5228-2666"},"institutions":[{"id":"https://openalex.org/I4210156583","display_name":"Laboratoire d'Informatique de Paris-Nord","ror":"https://ror.org/05g1zjw44","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I4210091279","https://openalex.org/I4210156583","https://openalex.org/I4210159245"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Gael Beck","raw_affiliation_strings":["Computer Science Laboratory (LIPN), University Paris-North-13, Villetaneuse, France"],"affiliations":[{"raw_affiliation_string":"Computer Science Laboratory (LIPN), University Paris-North-13, Villetaneuse, France","institution_ids":["https://openalex.org/I4210156583"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023422312","display_name":"Mustapha Lebbah","orcid":"https://orcid.org/0000-0001-7245-6371"},"institutions":[{"id":"https://openalex.org/I4210156583","display_name":"Laboratoire d'Informatique de Paris-Nord","ror":"https://ror.org/05g1zjw44","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I4210091279","https://openalex.org/I4210156583","https://openalex.org/I4210159245"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Mustapha Lebbah","raw_affiliation_strings":["Computer Science Laboratory (LIPN), University Paris-North-13, Villetaneuse, France"],"affiliations":[{"raw_affiliation_string":"Computer Science Laboratory (LIPN), University Paris-North-13, Villetaneuse, France","institution_ids":["https://openalex.org/I4210156583"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.074,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":19,"citation_normalized_percentile":{"value":0.865808,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":91},"biblio":{"volume":null,"issue":null,"first_page":"911","last_page":"916"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9998,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9998,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9937,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11719","display_name":"Data Quality and Management","score":0.9823,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/spark","display_name":"SPARK (programming language)","score":0.67663157},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48278534},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.41975272}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.79200196},{"id":"https://openalex.org/C2781215313","wikidata":"https://www.wikidata.org/wiki/Q3493345","display_name":"SPARK (programming language)","level":2,"score":0.67663157},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.65605056},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6439724},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.64004064},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.58681816},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48278534},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.45644432},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.43106395},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4258871},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4210647},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.41975272},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.41684255},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39281487},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38746625},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37385195},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3737602},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14558178},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258008","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://pure.aber.ac.uk/portal/en/publications/a-distributed-rough-set-theory-based-algorithm-for-an-efficient-big-data-preprocessing-under-the-spark-framework(6d4f3b9e-7954-49d1-aa26-1f8f87a02948).html","pdf_url":"https://research.aber.ac.uk/files/26109236/IEEEBigData2017_acceptedVersion.pdf","source":{"id":"https://openalex.org/S4306401660","display_name":"Aberystwyth Research portal (Aberystwyth University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I16038530","host_organization_name":"Aberystwyth University","host_organization_lineage":["https://openalex.org/I16038530"],"host_organization_lineage_names":["Aberystwyth University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false},{"is_oa":true,"landing_page_url":"https://pure.aber.ac.uk/ws/files/26109236/IEEEBigData2017_acceptedVersion.pdf","pdf_url":"https://pure.aber.ac.uk/ws/files/26109236/IEEEBigData2017_acceptedVersion.pdf","source":{"id":"https://openalex.org/S4306401660","display_name":"Aberystwyth Research portal (Aberystwyth University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I16038530","host_organization_name":"Aberystwyth University","host_organization_lineage":["https://openalex.org/I16038530"],"host_organization_lineage_names":["Aberystwyth University"],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://pure.aber.ac.uk/portal/en/publications/a-distributed-rough-set-theory-based-algorithm-for-an-efficient-big-data-preprocessing-under-the-spark-framework(6d4f3b9e-7954-49d1-aa26-1f8f87a02948).html","pdf_url":"https://research.aber.ac.uk/files/26109236/IEEEBigData2017_acceptedVersion.pdf","source":{"id":"https://openalex.org/S4306401660","display_name":"Aberystwyth Research portal (Aberystwyth University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I16038530","host_organization_name":"Aberystwyth University","host_organization_lineage":["https://openalex.org/I16038530"],"host_organization_lineage_names":["Aberystwyth University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":12,"referenced_works":["https://openalex.org/W1547566968","https://openalex.org/W1557923305","https://openalex.org/W1982861695","https://openalex.org/W2029307344","https://openalex.org/W2143451122","https://openalex.org/W2154185789","https://openalex.org/W2159128662","https://openalex.org/W2164364358","https://openalex.org/W2998216295","https://openalex.org/W3120740533","https://openalex.org/W4236642514","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W4244463999","https://openalex.org/W3083954504","https://openalex.org/W2884983377","https://openalex.org/W2806877302","https://openalex.org/W2734587838","https://openalex.org/W2362450124","https://openalex.org/W2352657000","https://openalex.org/W2126880743","https://openalex.org/W2052253960","https://openalex.org/W1933452047"],"abstract_inverted_index":{"Big":[0,192],"Data":[1,193],"reduction":[2],"is":[3,148],"a":[4,10,77,88,114,129,142,163],"main":[5],"point":[6],"of":[7,13,34,44,57,125,187],"interest":[8],"across":[9],"wide":[11],"variety":[12],"fields.":[14],"This":[15],"domain":[16],"was":[17,38],"further":[18],"investigated":[19],"when":[20],"the":[21,26,31,42,63,102,123,132,177,184],"difficulty":[22],"in":[23,128,158],"quickly":[24],"acquiring":[25],"most":[27,56],"useful":[28],"information":[29,61,99,197],"from":[30],"huge":[32],"amount":[33],"data":[35,45,65,118,133,174],"at":[36],"hand":[37],"encountered.":[39],"To":[40],"achieve":[41],"task":[43],"reduction,":[46],"specifically":[47],"feature":[48,78,91,144],"selection,":[49],"several":[50],"state-of-the-art":[51],"methods":[52],"were":[53],"proposed.":[54],"However,":[55,139],"them":[58],"require":[59],"additional":[60,137],"about":[62,87],"given":[64],"for":[66,154,172],"thresholding,":[67],"noise":[68],"levels":[69],"to":[70,85,116,121,191],"be":[71,110],"specified":[72],"or":[73],"they":[74],"even":[75],"need":[76],"ranking":[79],"procedure.":[80],"Thus,":[81],"it":[82],"seems":[83],"necessary":[84],"think":[86],"more":[89],"adequate":[90],"selection":[92,145],"technique":[93,115],"which":[94],"can":[95,109],"extract":[96],"features":[97,126],"using":[98,131],"contained":[100,127],"within":[101],"dataset":[103,130],"alone.":[104],"Rough":[105,167],"Set":[106,168],"Theory":[107,169],"(RST)":[108],"used":[111],"as":[112],"such":[113],"discover":[117],"dependencies":[119],"and":[120,151],"reduce":[122],"number":[124],"alone,":[134],"requiring":[135],"no":[136],"information.":[138],"despite":[140],"being":[141],"powerful":[143],"technique,":[146],"RST":[147,189],"computationally":[149],"expensive":[150],"only":[152],"practical":[153],"small":[155],"datasets.":[156],"Therefore,":[157],"this":[159],"paper,":[160],"we":[161],"present":[162],"novel":[164],"efficient":[165,185],"distributed":[166],"based":[170],"algorithm":[171],"large-scale":[173],"pre-processing":[175],"under":[176],"Spark":[178],"framework.":[179],"Our":[180],"experimental":[181],"results":[182],"show":[183],"applicability":[186],"our":[188],"solution":[190],"without":[194],"any":[195],"significant":[196],"loss.":[198]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2783605012","counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":2}],"updated_date":"2024-12-29T17:56:14.059901","created_date":"2018-01-26"}