{"id":"https://openalex.org/W2942204973","doi":"https://doi.org/10.1109/access.2019.2908776","title":"IEEE Access Special Section Editorial: Data Mining and Granular Computing in Big Data and Knowledge Processing","display_name":"IEEE Access Special Section Editorial: Data Mining and Granular Computing in Big Data and Knowledge Processing","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2942204973","doi":"https://doi.org/10.1109/access.2019.2908776","mag":"2942204973"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2908776","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2908776","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08694036.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08694036.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069969191","display_name":"Weiping Ding","orcid":"https://orcid.org/0000-0002-3180-7347"},"institutions":[{"id":"https://openalex.org/I199305430","display_name":"Nantong University","ror":"https://ror.org/02afcvw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I199305430"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weiping Ding","raw_affiliation_strings":["Nantong University, Nantong, China"],"affiliations":[{"raw_affiliation_string":"Nantong University, Nantong, China","institution_ids":["https://openalex.org/I199305430"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010638666","display_name":"Gary G. Yen","orcid":"https://orcid.org/0000-0001-8851-5348"},"institutions":[{"id":"https://openalex.org/I115475287","display_name":"Oklahoma State University","ror":"https://ror.org/01g9vbr38","country_code":"US","type":"education","lineage":["https://openalex.org/I115475287"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gary G. Yen","raw_affiliation_strings":["Oklahoma State University, Stillwater, OK, USA"],"affiliations":[{"raw_affiliation_string":"Oklahoma State University, Stillwater, OK, USA","institution_ids":["https://openalex.org/I115475287"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011976667","display_name":"Gleb Beliakov","orcid":"https://orcid.org/0000-0002-9841-5292"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Gleb Beliakov","raw_affiliation_strings":["Deakin University, Burwood, VIC, Australia"],"affiliations":[{"raw_affiliation_string":"Deakin University, Burwood, VIC, Australia","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075541426","display_name":"Isaac Triguero","orcid":"https://orcid.org/0000-0002-0150-0651"},"institutions":[{"id":"https://openalex.org/I142263535","display_name":"University of Nottingham","ror":"https://ror.org/01ee9ar58","country_code":"GB","type":"education","lineage":["https://openalex.org/I142263535"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Isaac Triguero","raw_affiliation_strings":["University of Nottingham, Nottingham, U.K"],"affiliations":[{"raw_affiliation_string":"University of Nottingham, Nottingham, U.K","institution_ids":["https://openalex.org/I142263535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036928886","display_name":"Mahardhika Pratama","orcid":"https://orcid.org/0000-0001-6531-5087"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Mahardhika Pratama","raw_affiliation_strings":["Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000755750","display_name":"Xiangliang Zhang","orcid":"https://orcid.org/0000-0002-3574-5665"},"institutions":[{"id":"https://openalex.org/I71920554","display_name":"King Abdullah University of Science and Technology","ror":"https://ror.org/01q3tbs38","country_code":"SA","type":"education","lineage":["https://openalex.org/I71920554"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Xiangliang Zhang","raw_affiliation_strings":["King Abdullah University of Science and Technology, Thuwal, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"King Abdullah University of Science and Technology, Thuwal, Saudi Arabia","institution_ids":["https://openalex.org/I71920554"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100346665","display_name":"Hongjun Li","orcid":"https://orcid.org/0000-0001-7500-4979"},"institutions":[{"id":"https://openalex.org/I199305430","display_name":"Nantong University","ror":"https://ror.org/02afcvw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I199305430"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongjun Li","raw_affiliation_strings":["Nantong University, Nantong, China"],"affiliations":[{"raw_affiliation_string":"Nantong University, Nantong, China","institution_ids":["https://openalex.org/I199305430"]}]}],"institutions":[],"countries_distinct_count":6,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5069969191"],"corresponding_institution_ids":["https://openalex.org/I199305430"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.7759,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.73719454,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"7","issue":null,"first_page":"47682","last_page":"47686"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.982200026512146,"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":0.982200026512146,"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":0.9624999761581421,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.8544244170188904},{"id":"https://openalex.org/keywords/granular-computing","display_name":"Granular computing","score":0.8397024869918823},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.788834273815155},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.6160275936126709},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.5787929892539978},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5538238883018494},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.5478158593177795},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5410792231559753},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5169117450714111},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5133734941482544},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4809359908103943},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4608795940876007},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.46064406633377075},{"id":"https://openalex.org/keywords/data-processing","display_name":"Data processing","score":0.4390212297439575},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32320088148117065},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.16240349411964417},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.12908396124839783}],"concepts":[{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.8544244170188904},{"id":"https://openalex.org/C17209119","wikidata":"https://www.wikidata.org/wiki/Q5596712","display_name":"Granular computing","level":3,"score":0.8397024869918823},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.788834273815155},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.6160275936126709},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.5787929892539978},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5538238883018494},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.5478158593177795},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5410792231559753},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5169117450714111},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5133734941482544},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4809359908103943},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4608795940876007},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.46064406633377075},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.4390212297439575},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32320088148117065},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.16240349411964417},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.12908396124839783},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2908776","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2908776","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08694036.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:220a53d55cf749f194da042181f0ec39","is_oa":true,"landing_page_url":"https://doaj.org/article/220a53d55cf749f194da042181f0ec39","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 47682-47686 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2908776","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2908776","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08694036.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.550000011920929,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2942204973.pdf","grobid_xml":"https://content.openalex.org/works/W2942204973.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1795409297","https://openalex.org/W2013421631","https://openalex.org/W2282249876","https://openalex.org/W2907231604","https://openalex.org/W2264129129","https://openalex.org/W2765911721","https://openalex.org/W2534449155","https://openalex.org/W3091858790","https://openalex.org/W2922513649","https://openalex.org/W4239687749"],"abstract_inverted_index":{"Data":[0],"mining":[1,100,183,207],"has":[2,81,126],"actively":[3],"contributed":[4],"to":[5,84,92,193],"solving":[6],"many":[7],"real-world":[8],"problems":[9,101],"with":[10],"a":[11,30,78,111,151],"variety":[12],"of":[13,32,68,154,167,205],"techniques.":[14],"Traditional":[15],"approaches":[16],"in":[17,56,65,102,132,178,211],"this":[18],"field":[19,220],"are":[20,63,161],"classification,":[21],"clustering":[22],"and":[23,41,96,105,117,130,140,157,195,208,214,226,236],"regression.":[24],"During":[25],"the":[26,57,66,86,94,165,179],"last":[27],"few":[28],"years":[29],"number":[31],"chal-lenges":[33],"have":[34],"emerged,":[35],"such":[36],"as":[37],"imbalanced":[38],"data,":[39,70],"multi-label":[40],"multi-instance":[42],"problems,":[43],"low":[44],"quality":[45],"and/or":[46],"noisy":[47],"data":[48,99,104,119,134,148,174,182,197,206,213],"or":[49],"semi-supervised":[50],"learning,":[51],"among":[52],"others":[53],"[item":[54,143,176],"1)":[55],"Appendix].":[58,146,180],"When":[59],"these":[60],"non-standard":[61],"scenarios":[62],"encountered":[64],"realm":[67],"big":[69,103,173,212],"it":[71,189],"remains":[72],"an":[73,218],"uncharted":[74],"research":[75,224],"territory,":[76],"although":[77],"growing":[79],"effort":[80],"been":[82],"made":[83],"break":[85],"limits.":[87],"The":[88,203],"current":[89],"trend":[90],"is":[91,190,217],"address":[93],"classical":[95],"newly":[97],"emerging":[98,219],"knowledge":[106,215],"processing.":[107],"Granular":[108],"computing":[109,169,201,210],"provides":[110],"powerful":[112],"tool":[113],"for":[114],"multiple":[115,223],"granularity":[116,123],"multiple-view":[118],"analysis":[120],"at":[121],"differ-ent":[122],"levels,":[124],"which":[125,221],"demonstrated":[127],"strong":[128],"capabil-ities":[129],"advantages":[131],"intelligent":[133],"analysis,":[135],"pattern":[136],"recog-nition,":[137],"machine":[138],"learning":[139],"uncertain":[141,156],"reasoning":[142],"2)":[144],"inthe":[145],"Big":[147,181],"often":[149,191],"contains":[150],"significant":[152],"amount":[153],"unstructured,":[155],"imprecise":[158],"data.":[159],"There":[160],"new":[162],"challenges":[163],"regarding":[164],"scalability":[166],"granular":[168,209],"when":[170],"addressing":[171],"very":[172],"sets":[175],"3)":[177],"relies":[184],"on":[185,198],"distributed":[186],"computational":[187],"strate-gies;":[188],"impossible":[192],"store":[194],"process":[196],"one":[199],"single":[200],"node.":[202],"exploration":[204],"processing":[216],"crosses":[222],"disciplines":[225],"industry":[227],"domains,":[228],"including":[229],"transportation,":[230],"communications,":[231],"social":[232],"network,":[233],"medical":[234],"health,":[235],"so":[237],"on.":[238]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
