{"id":"https://openalex.org/W4291011184","doi":"https://doi.org/10.3390/info13080385","title":"Multi-Target Rough Sets and Their Approximation Computation with Dynamic Target Sets","display_name":"Multi-Target Rough Sets and Their Approximation Computation with Dynamic Target Sets","publication_year":2022,"publication_date":"2022-08-11","ids":{"openalex":"https://openalex.org/W4291011184","doi":"https://doi.org/10.3390/info13080385"},"language":"en","primary_location":{"id":"doi:10.3390/info13080385","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info13080385","pdf_url":"https://www.mdpi.com/2078-2489/13/8/385/pdf?version=1660898676","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/13/8/385/pdf?version=1660898676","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085413867","display_name":"Wenbin Zheng","orcid":"https://orcid.org/0000-0003-3946-2184"},"institutions":[{"id":"https://openalex.org/I9356336","display_name":"Minnan Normal University","ror":"https://ror.org/02vj1vm13","country_code":"CN","type":"education","lineage":["https://openalex.org/I9356336"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenbin Zheng","raw_affiliation_strings":["Key Laboratory of Data Science and Intelligence Application, Fujian Province University, Zhangzhou 363000, China","School of Computer Science, Minnan Normal University, Zhangzhou 363000, China"],"raw_orcid":"https://orcid.org/0000-0003-3946-2184","affiliations":[{"raw_affiliation_string":"Key Laboratory of Data Science and Intelligence Application, Fujian Province University, Zhangzhou 363000, China","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science, Minnan Normal University, Zhangzhou 363000, China","institution_ids":["https://openalex.org/I9356336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100657117","display_name":"Jinjin Li","orcid":"https://orcid.org/0000-0001-9947-6858"},"institutions":[{"id":"https://openalex.org/I9356336","display_name":"Minnan Normal University","ror":"https://ror.org/02vj1vm13","country_code":"CN","type":"education","lineage":["https://openalex.org/I9356336"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinjin Li","raw_affiliation_strings":["School of Mathematics and Statistics, Minnan Normal University, Zhangzhou 363000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Minnan Normal University, Zhangzhou 363000, China","institution_ids":["https://openalex.org/I9356336"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036870468","display_name":"Shujiao Liao","orcid":"https://orcid.org/0000-0003-3640-3648"},"institutions":[{"id":"https://openalex.org/I9356336","display_name":"Minnan Normal University","ror":"https://ror.org/02vj1vm13","country_code":"CN","type":"education","lineage":["https://openalex.org/I9356336"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shujiao Liao","raw_affiliation_strings":["School of Mathematics and Statistics, Minnan Normal University, Zhangzhou 363000, China"],"raw_orcid":"https://orcid.org/0000-0003-3640-3648","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Minnan Normal University, Zhangzhou 363000, China","institution_ids":["https://openalex.org/I9356336"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5036870468","https://openalex.org/A5085413867"],"corresponding_institution_ids":["https://openalex.org/I9356336"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1782},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1782},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11243842,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":"8","first_page":"385","last_page":"385"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9998000264167786,"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":0.9998000264167786,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9976999759674072,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9465000033378601,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/rough-set","display_name":"Rough set","score":0.8606715798377991},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6629173159599304},{"id":"https://openalex.org/keywords/decision-table","display_name":"Decision table","score":0.6181386113166809},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6165510416030884},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6022290587425232},{"id":"https://openalex.org/keywords/dominance-based-rough-set-approach","display_name":"Dominance-based rough set approach","score":0.5848821401596069},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5255348086357117},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5044382810592651},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.5030974745750427},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47533372044563293},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4731280207633972},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.310718297958374},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15188351273536682}],"concepts":[{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.8606715798377991},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6629173159599304},{"id":"https://openalex.org/C172967692","wikidata":"https://www.wikidata.org/wiki/Q747762","display_name":"Decision table","level":3,"score":0.6181386113166809},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6165510416030884},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6022290587425232},{"id":"https://openalex.org/C39105242","wikidata":"https://www.wikidata.org/wiki/Q5290286","display_name":"Dominance-based rough set approach","level":3,"score":0.5848821401596069},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5255348086357117},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5044382810592651},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.5030974745750427},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47533372044563293},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4731280207633972},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.310718297958374},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15188351273536682},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/info13080385","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info13080385","pdf_url":"https://www.mdpi.com/2078-2489/13/8/385/pdf?version=1660898676","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c3ad13313c3345dba67bfcba1dff207c","is_oa":true,"landing_page_url":"https://doaj.org/article/c3ad13313c3345dba67bfcba1dff207c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information, Vol 13, Iss 8, p 385 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2078-2489/13/8/385/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/info13080385","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information; Volume 13; Issue 8; Pages: 385","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/info13080385","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info13080385","pdf_url":"https://www.mdpi.com/2078-2489/13/8/385/pdf?version=1660898676","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G1806932936","display_name":"\u6570\u636e\u62d3\u6251\u7a7a\u95f4\u7684\u6781\u5c0f\u57fa\uff08\u5b50\u57fa\uff09\u7b97\u6cd5\u53ca\u5176\u5e94\u7528\u7684\u7814\u7a76","funder_award_id":"11871259","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3436105776","display_name":"\u52a8\u6001\u8986\u76d6\u4fe1\u606f\u7cfb\u7edf\u7684\u7279\u5f81\u9009\u62e9\u7814\u7a76","funder_award_id":"2022J01912","funder_id":"https://openalex.org/F4320321878","funder_display_name":"Natural Science Foundation of Fujian Province"},{"id":"https://openalex.org/G4271181791","display_name":null,"funder_award_id":"12101289","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5374718714","display_name":null,"funder_award_id":"61379021","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7693756926","display_name":null,"funder_award_id":"2022J01306","funder_id":"https://openalex.org/F4320321878","funder_display_name":"Natural Science Foundation of Fujian Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321878","display_name":"Natural Science Foundation of Fujian Province","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4291011184.pdf","grobid_xml":"https://content.openalex.org/works/W4291011184.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1997362234","https://openalex.org/W2016929372","https://openalex.org/W2049157258","https://openalex.org/W2057532020","https://openalex.org/W2114315281","https://openalex.org/W2191800066","https://openalex.org/W2340020088","https://openalex.org/W2470167798","https://openalex.org/W2552836761","https://openalex.org/W2582026797","https://openalex.org/W2605997098","https://openalex.org/W2609793245","https://openalex.org/W2750802903","https://openalex.org/W2778359823","https://openalex.org/W2792516156","https://openalex.org/W2796330245","https://openalex.org/W2827042384","https://openalex.org/W2883654649","https://openalex.org/W2888781447","https://openalex.org/W2908473781","https://openalex.org/W2955883555","https://openalex.org/W3002831548","https://openalex.org/W3010203991","https://openalex.org/W3037411234","https://openalex.org/W3090314981","https://openalex.org/W3128841777","https://openalex.org/W3139167884","https://openalex.org/W3140459407","https://openalex.org/W3155562149","https://openalex.org/W3164727871","https://openalex.org/W3175102871","https://openalex.org/W3195285466","https://openalex.org/W3197217164","https://openalex.org/W4205754927","https://openalex.org/W4244166797","https://openalex.org/W6805844331"],"related_works":["https://openalex.org/W2157126134","https://openalex.org/W2369031945","https://openalex.org/W139457133","https://openalex.org/W1970534408","https://openalex.org/W74108157","https://openalex.org/W2165634587","https://openalex.org/W2963142056","https://openalex.org/W2361933495","https://openalex.org/W160161930","https://openalex.org/W1547847669"],"abstract_inverted_index":{"Multi-label":[0],"learning":[1,32,55],"has":[2,89,121,131,136],"become":[3],"a":[4,41,46,50,84,155,161],"hot":[5],"topic":[6],"in":[7,19],"recent":[8],"years,":[9],"attracting":[10],"scholars\u2019":[11],"attention,":[12],"including":[13],"applying":[14],"the":[15,26,35,57,95,110,127,150,170,179],"rough":[16,27,36,58,85,117],"set":[17,28,59,86,118,129],"model":[18,29,60,87,112,119],"multi-label":[20,31,54,142],"learning.":[21,143],"Exciting":[22],"works":[23],"that":[24,79,88,120,130],"apply":[25],"into":[30],"usually":[33],"adapt":[34],"sets":[37],"model\u2019s":[38],"purpose":[39],"for":[40],"single":[42],"decision":[43],"table":[44,48],"to":[45,63,101,141,148],"multi-decision":[47],"with":[49],"conservative":[51],"strategy.":[52],"However,":[53],"enforces":[56],"which":[61],"wants":[62],"be":[64],"applied":[65,140],"considering":[66],"multiple":[67,90,122,132],"target":[68,91,99,123,162],"concepts,":[69],"and":[70,93,134,157,168,176],"there":[71],"is":[72,164],"label":[73,103],"correlation":[74,104],"among":[75,98,105],"labels":[76],"naturally.":[77],"For":[78],"proposal,":[80],"this":[81],"paper":[82],"proposes":[83],"concepts":[92,100,124],"considers":[94],"similarity":[96],"relationships":[97],"capture":[102],"labels.":[106],"The":[107,116,174],"properties":[108],"of":[109,152,178],"proposed":[111],"are":[113,182],"also":[114],"investigated.":[115],"can":[125],"handle":[126],"data":[128],"decisions,":[133],"it":[135],"inherent":[137],"advantages":[138],"when":[139,160],"Moreover,":[144],"we":[145],"consider":[146],"how":[147],"compute":[149],"approximations":[151],"GMTRSs":[153],"under":[154],"static":[156],"dynamic":[158],"situation":[159],"concept":[163],"added":[165],"or":[166],"removed":[167],"derive":[169],"corresponding":[171],"algorithms,":[172],"respectively.":[173],"efficiency":[175],"validity":[177],"designed":[180],"algorithms":[181],"verified":[183],"by":[184],"experiments.":[185]},"counts_by_year":[],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2022-08-13T00:00:00"}
