{"id":"https://openalex.org/W2995274570","doi":"https://doi.org/10.1109/tencon.2019.8929668","title":"Fuzzy Rough Discernibility Matrix Based Feature Subset Selection With MapReduce","display_name":"Fuzzy Rough Discernibility Matrix Based Feature Subset Selection With MapReduce","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2995274570","doi":"https://doi.org/10.1109/tencon.2019.8929668","mag":"2995274570"},"language":"en","primary_location":{"id":"doi:10.1109/tencon.2019.8929668","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon.2019.8929668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON)","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/A5072626440","display_name":"N. Pavani","orcid":null},"institutions":[{"id":"https://openalex.org/I36893310","display_name":"University of Hyderabad","ror":"https://ror.org/04a7rxb17","country_code":"IN","type":"education","lineage":["https://openalex.org/I36893310"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Neeli Lakshmi Pavani","raw_affiliation_strings":["School of CIS, University of Hyderabad, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"School of CIS, University of Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I36893310"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001486679","display_name":"Pandu Sowkuntla","orcid":"https://orcid.org/0000-0001-9656-6946"},"institutions":[{"id":"https://openalex.org/I36893310","display_name":"University of Hyderabad","ror":"https://ror.org/04a7rxb17","country_code":"IN","type":"education","lineage":["https://openalex.org/I36893310"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pandu Sowkuntla","raw_affiliation_strings":["School of CIS, University of Hyderabad, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"School of CIS, University of Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I36893310"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090812966","display_name":"K. Swarupa Rani","orcid":"https://orcid.org/0000-0002-9529-2688"},"institutions":[{"id":"https://openalex.org/I36893310","display_name":"University of Hyderabad","ror":"https://ror.org/04a7rxb17","country_code":"IN","type":"education","lineage":["https://openalex.org/I36893310"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"K. Swarupa Rani","raw_affiliation_strings":["School of CIS, University of Hyderabad, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"School of CIS, University of Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I36893310"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009848742","display_name":"P. S. V. S. Sai Prasad","orcid":null},"institutions":[{"id":"https://openalex.org/I36893310","display_name":"University of Hyderabad","ror":"https://ror.org/04a7rxb17","country_code":"IN","type":"education","lineage":["https://openalex.org/I36893310"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"P.S.V.S Sai Prasad","raw_affiliation_strings":["School of CIS, University of Hyderabad, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"School of CIS, University of Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I36893310"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5072626440"],"corresponding_institution_ids":["https://openalex.org/I36893310"],"apc_list":null,"apc_paid":null,"fwci":0.194,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.56872932,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"59","issue":null,"first_page":"389","last_page":"394"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9998999834060669,"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":0.9998999834060669,"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/T10050","display_name":"Multi-Criteria Decision Making","score":0.9904000163078308,"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"}},{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9890000224113464,"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/feature-selection","display_name":"Feature selection","score":0.7215924263000488},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.637840986251831},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6229161620140076},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6115083694458008},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5188959240913391},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5019769668579102},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5002346038818359},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.49298450350761414},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4837181866168976},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.4546937346458435},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41585463285446167}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7215924263000488},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.637840986251831},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6229161620140076},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6115083694458008},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5188959240913391},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5019769668579102},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5002346038818359},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.49298450350761414},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4837181866168976},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.4546937346458435},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41585463285446167},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon.2019.8929668","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon.2019.8929668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6100000143051147}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W119268588","https://openalex.org/W1521417790","https://openalex.org/W1570069324","https://openalex.org/W2002680690","https://openalex.org/W2004075750","https://openalex.org/W2019995001","https://openalex.org/W2027654459","https://openalex.org/W2079680557","https://openalex.org/W2082173396","https://openalex.org/W2090738500","https://openalex.org/W2092044939","https://openalex.org/W2092845575","https://openalex.org/W2128771953","https://openalex.org/W2137205163","https://openalex.org/W2162364423","https://openalex.org/W2173440868","https://openalex.org/W2416404380","https://openalex.org/W2542459869","https://openalex.org/W2556225449","https://openalex.org/W2766239046","https://openalex.org/W2794427941","https://openalex.org/W2794679165","https://openalex.org/W3120740533","https://openalex.org/W4255833381"],"related_works":["https://openalex.org/W2392963705","https://openalex.org/W2382278777","https://openalex.org/W2107349454","https://openalex.org/W2353240132","https://openalex.org/W4386564352","https://openalex.org/W2952668426","https://openalex.org/W2978519593","https://openalex.org/W2102746356","https://openalex.org/W4390066334","https://openalex.org/W2096751418"],"abstract_inverted_index":{"Fuzzy-rough":[0],"set":[1,74],"theory":[2],"(FRST)":[3],"is":[4,80],"a":[5,81,84,108],"hybridization":[6],"of":[7,47,53,67,83,91,126],"fuzzy":[8],"sets":[9,12,29],"with":[10,13,57],"rough":[11],"applications":[14],"to":[15,33,39],"attribute":[16,76,105,132],"reduction":[17,106,133],"in":[18,27,130],"hybrid":[19,120],"decision":[20,36,121],"systems.":[21],"The":[22],"existing":[23],"reduct":[24],"computation":[25],"approaches":[26],"fuzzy-rough":[28,73,93,104],"are":[30],"not":[31],"scalable":[32,54,72,131],"large":[34,117],"scale":[35,118],"systems":[37,122],"owing":[38],"higher":[40],"space":[41],"complexity":[42],"requirements.":[43],"Iterative":[44],"MapReduce":[45],"framework":[46],"Apache":[48],"Spark":[49],"facilitates":[50],"the":[51,68,89,124,127],"development":[52],"distributed":[55,92,103],"algorithms":[56],"fault":[58],"tolerance.":[59],"This":[60],"work":[61],"introduces":[62],"algorithm":[63,79],"MR_FRDM_SBE":[64,78],"as":[65],"one":[66],"first":[69],"attempts":[70],"towards":[71],"based":[75,102],"reduction.":[77],"combination":[82],"novel":[85],"incremental":[86],"approach":[87,129],"for":[88],"construction":[90],"discernibility":[94,109],"matrix":[95],"and":[96,134],"Sequential":[97],"Backward":[98],"Elimination":[99],"control":[100],"strategy":[101],"using":[107,116],"matrix.":[110],"A":[111],"comparative":[112],"experimental":[113],"study":[114],"conducted":[115],"benchmark":[119],"demonstrated":[123],"relevance":[125],"proposed":[128],"better":[135],"classification":[136],"model":[137],"construction.":[138]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
