{"id":"https://openalex.org/W2074369800","doi":"https://doi.org/10.4018/ijrsda.2014010102","title":"Attribute Reduction Using Bayesian Decision Theoretic Rough Set Models","display_name":"Attribute Reduction Using Bayesian Decision Theoretic Rough Set Models","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2074369800","doi":"https://doi.org/10.4018/ijrsda.2014010102","mag":"2074369800"},"language":"en","primary_location":{"id":"doi:10.4018/ijrsda.2014010102","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijrsda.2014010102","pdf_url":null,"source":{"id":"https://openalex.org/S4210215979","display_name":"International Journal of Rough Sets and Data Analysis","issn_l":"2334-4598","issn":["2334-4598","2334-4601"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Rough Sets and Data Analysis","raw_type":"journal-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/A5112080475","display_name":"Sharmistha Halder","orcid":null},"institutions":[{"id":"https://openalex.org/I72677176","display_name":"Tripura University","ror":"https://ror.org/05xqycm14","country_code":"IN","type":"education","lineage":["https://openalex.org/I72677176"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Sharmistha Bhattacharya Halder","raw_affiliation_strings":["Department of Mathematics, Tripura University, Bikramnagar, Tripura, India"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Tripura University, Bikramnagar, Tripura, India","institution_ids":["https://openalex.org/I72677176"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017295713","display_name":"Kalyani Debnath","orcid":null},"institutions":[{"id":"https://openalex.org/I72677176","display_name":"Tripura University","ror":"https://ror.org/05xqycm14","country_code":"IN","type":"education","lineage":["https://openalex.org/I72677176"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kalyani Debnath","raw_affiliation_strings":["Tripura University, Bikramnagar, Tripura, India"],"affiliations":[{"raw_affiliation_string":"Tripura University, Bikramnagar, Tripura, India","institution_ids":["https://openalex.org/I72677176"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5112080475"],"corresponding_institution_ids":["https://openalex.org/I72677176"],"apc_list":null,"apc_paid":null,"fwci":1.0682,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.78253952,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"1","issue":"1","first_page":"15","last_page":"31"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9613999724388123,"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/T10050","display_name":"Multi-Criteria Decision Making","score":0.9211999773979187,"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/rough-set","display_name":"Rough set","score":0.8832321166992188},{"id":"https://openalex.org/keywords/dominance-based-rough-set-approach","display_name":"Dominance-based rough set approach","score":0.7280253171920776},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.6706453561782837},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5467055439949036},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5162777304649353},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5087948441505432},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47335243225097656},{"id":"https://openalex.org/keywords/decision-rule","display_name":"Decision rule","score":0.4574945867061615},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4493647813796997},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.43426424264907837},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.41101160645484924},{"id":"https://openalex.org/keywords/decision-model","display_name":"Decision model","score":0.4104391634464264},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3904193341732025}],"concepts":[{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.8832321166992188},{"id":"https://openalex.org/C39105242","wikidata":"https://www.wikidata.org/wiki/Q5290286","display_name":"Dominance-based rough set approach","level":3,"score":0.7280253171920776},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.6706453561782837},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5467055439949036},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5162777304649353},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5087948441505432},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47335243225097656},{"id":"https://openalex.org/C84839998","wikidata":"https://www.wikidata.org/wiki/Q5249245","display_name":"Decision rule","level":2,"score":0.4574945867061615},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4493647813796997},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43426424264907837},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.41101160645484924},{"id":"https://openalex.org/C59594135","wikidata":"https://www.wikidata.org/wiki/Q5249242","display_name":"Decision model","level":2,"score":0.4104391634464264},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3904193341732025},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.4018/ijrsda.2014010102","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijrsda.2014010102","pdf_url":null,"source":{"id":"https://openalex.org/S4210215979","display_name":"International Journal of Rough Sets and Data Analysis","issn_l":"2334-4598","issn":["2334-4598","2334-4601"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Rough Sets and Data Analysis","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8299999833106995,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1521291086","https://openalex.org/W1543832863","https://openalex.org/W1557923305","https://openalex.org/W1591618909","https://openalex.org/W1605308969","https://openalex.org/W1606022329","https://openalex.org/W1822488028","https://openalex.org/W1943154432","https://openalex.org/W1964228588","https://openalex.org/W1969463949","https://openalex.org/W1980861610","https://openalex.org/W1997362234","https://openalex.org/W2009653394","https://openalex.org/W2024638676","https://openalex.org/W2045358009","https://openalex.org/W2054804336","https://openalex.org/W2088296434","https://openalex.org/W2091298464","https://openalex.org/W2101285186","https://openalex.org/W2143451122","https://openalex.org/W2176071742","https://openalex.org/W2340020088","https://openalex.org/W3017143921","https://openalex.org/W4232953319","https://openalex.org/W4255833381","https://openalex.org/W6634294544"],"related_works":["https://openalex.org/W4214891796","https://openalex.org/W2165634587","https://openalex.org/W2963142056","https://openalex.org/W2389890090","https://openalex.org/W1768477318","https://openalex.org/W2519291612","https://openalex.org/W2370118692","https://openalex.org/W2219741085","https://openalex.org/W2365612261","https://openalex.org/W1787812828"],"abstract_inverted_index":{"Bayesian":[0,21,45,65,179,193],"Decision":[1],"theoretic":[2,23,67,197],"rough":[3,24,48,68,180,198],"set":[4,25,49,69,181,199],"has":[5,26],"been":[6,27],"invented":[7],"by":[8,17,90,158],"the":[9,14,18,56,108,115,119,125,140,159,166],"author.":[10],"In":[11,151],"this":[12,91,102,113,152,187],"paper":[13,153],"attribute":[15,36,86,121,142,154],"reduction":[16,37,87,155],"aid":[19],"of":[20,30,58,80,161,178],"decision":[22,66,184,196],"studied.":[28],"Lot":[29],"other":[31,75,96],"methods":[32],"are":[33,139],"there":[34],"for":[35],"such":[38],"as":[39],"Variable":[40],"precision":[41,145],"method,":[42,46],"probabilistic":[43],"approach,":[44],"Pawlaks":[47],"method":[50,93,103,114,146,194],"using":[51],"Boolean":[52],"function.":[53],"But":[54],"with":[55],"help":[57,160],"some":[59],"example":[60,79],"it":[61],"is":[62,83,88,99,124,156,174],"shown":[63,100],"that":[64,101],"model":[70,132,173,177,182],"gives":[71,104,189],"better":[72,105,190],"result":[73,106,191],"than":[74,107,192],"method.":[76,97,200],"Lastly":[77],"an":[78],"HIV":[81],"/AIDS":[82],"taken":[84],"and":[85,94,143,169,183,195],"done":[89,157],"new":[92],"various":[95],"It":[98],"previously":[109],"defined":[110],"methods.":[111],"By":[112],"authors":[116],"get":[117],"only":[118],"reduced":[120,141],"age":[122,133,136],"which":[123],"best":[126],"significant":[127],"attribute.":[128],"Though":[129],"in":[130],"Pawlak":[131],"sex":[134],"or":[135],"living":[137],"status":[138],"variable":[144],"fails":[147],"to":[148],"work":[149],"here.":[150],"discernibility":[162],"matrix":[163],"after":[164],"determining":[165],"positive,":[167],"boundary":[168],"negative":[170],"region.":[171],"This":[172],"a":[175],"hybrid":[176],"theory.":[185],"So":[186],"technique":[188]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
