{"id":"https://openalex.org/W4386702455","doi":"https://doi.org/10.1145/3594300.3594308","title":"FWNRS:A Fast Attribute Reduction Algorithm based on Weighted Neighborhood Rough Set","display_name":"FWNRS:A Fast Attribute Reduction Algorithm based on Weighted Neighborhood Rough Set","publication_year":2023,"publication_date":"2023-04-07","ids":{"openalex":"https://openalex.org/W4386702455","doi":"https://doi.org/10.1145/3594300.3594308"},"language":"en","primary_location":{"id":"doi:10.1145/3594300.3594308","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1145/3594300.3594308","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 8th International Conference on Mathematics and Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","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/A5080535357","display_name":"Xiaoli Peng","orcid":"https://orcid.org/0000-0002-3436-2574"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]},{"id":"https://openalex.org/I4210086059","display_name":"Sichuan University of Arts and Science","ror":"https://ror.org/00erq7915","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210086059"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoli Peng","raw_affiliation_strings":["College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, China and Institute of Intelligent Manufacturing Technology, Sichuan University of Arts and Science, China"],"raw_orcid":"https://orcid.org/0000-0002-3436-2574","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, China and Institute of Intelligent Manufacturing Technology, Sichuan University of Arts and Science, China","institution_ids":["https://openalex.org/I10535382","https://openalex.org/I4210086059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014405252","display_name":"Ping Wang","orcid":"https://orcid.org/0000-0003-1527-7478"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Wang","raw_affiliation_strings":["Key Laboratory of Industrial Internet of Things and Networked Control, Ministry of Education, Chongqing University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0003-1527-7478","affiliations":[{"raw_affiliation_string":"Key Laboratory of Industrial Internet of Things and Networked Control, Ministry of Education, Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078517869","display_name":"Yabin Shao","orcid":"https://orcid.org/0000-0003-1001-7132"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yabin Shao","raw_affiliation_strings":["College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0003-1001-7132","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083752026","display_name":"Chenggen Pu","orcid":"https://orcid.org/0000-0002-1272-1871"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenggen Pu","raw_affiliation_strings":["College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0002-1272-1871","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085319644","display_name":"Jie Qian","orcid":"https://orcid.org/0000-0003-3382-8245"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Qian","raw_affiliation_strings":["College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0003-3382-8245","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1795255,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"42","last_page":"46"},"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":0.9598000049591064,"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/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.9509000182151794,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.7611473798751831},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.7469578385353088},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6318279504776001},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5864744782447815},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.49503153562545776},{"id":"https://openalex.org/keywords/algorithm-design","display_name":"Algorithm design","score":0.4418301284313202},{"id":"https://openalex.org/keywords/set-theory","display_name":"Set theory","score":0.4134688377380371},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3226575255393982},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31696587800979614},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24424558877944946}],"concepts":[{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.7611473798751831},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.7469578385353088},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6318279504776001},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5864744782447815},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.49503153562545776},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.4418301284313202},{"id":"https://openalex.org/C153046414","wikidata":"https://www.wikidata.org/wiki/Q12482","display_name":"Set theory","level":3,"score":0.4134688377380371},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3226575255393982},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31696587800979614},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24424558877944946},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3594300.3594308","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1145/3594300.3594308","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 8th International Conference on Mathematics and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5869566131","display_name":null,"funder_award_id":"2021YFB3301000","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W165079900","https://openalex.org/W1983105620","https://openalex.org/W2018530017","https://openalex.org/W2035374712","https://openalex.org/W2078975293","https://openalex.org/W2158633287","https://openalex.org/W2313866064","https://openalex.org/W2517012834","https://openalex.org/W2557776595","https://openalex.org/W2898603484","https://openalex.org/W2901011786","https://openalex.org/W2911253711","https://openalex.org/W2922513649","https://openalex.org/W2991640799","https://openalex.org/W3004671851","https://openalex.org/W3029713334","https://openalex.org/W3036852947","https://openalex.org/W3134939203","https://openalex.org/W3172174372","https://openalex.org/W4284992467","https://openalex.org/W4293562735"],"related_works":["https://openalex.org/W2387804527","https://openalex.org/W2103840922","https://openalex.org/W2355968574","https://openalex.org/W2107349454","https://openalex.org/W2166201494","https://openalex.org/W2386642237","https://openalex.org/W2376925652","https://openalex.org/W2389210842","https://openalex.org/W2359327418","https://openalex.org/W2946250706"],"abstract_inverted_index":{"The":[0,81,106,119,178],"weighted":[1],"neighborhood":[2,9,78,87,147],"rough":[3,10],"set":[4,11,124],"(WNRS)":[5],"is":[6,47,84,109,122,150,184],"a":[7,57],"novel":[8],"model":[12],"which":[13,192],"doesn\u2019t":[14],"treat":[15],"all":[16,194],"attributes":[17],"as":[18],"equally":[19],"important.":[20],"It":[21],"performs":[22],"well":[23],"in":[24,37,66],"attribute":[25,39,59,157,196],"reduction":[26,40,60,158,197],"on":[27,42,63,161],"real-valued":[28],"data.":[29],"However,":[30],"there":[31],"are":[32,170,193],"still":[33],"so":[34],"many":[35],"calculations":[36],"the":[38,77,86,95,99,111,116,125,129,135,139,146,155,162,174,188],"based":[41,62,160],"WNRS":[43,64],"that":[44,182],"its":[45,103],"efficiency":[46,175],"not":[48],"high":[49],"enough.":[50],"To":[51],"solve":[52],"this":[53,67],"drawback,":[54],"we":[55,70,153],"propose":[56,71],"fast":[58,73,156,163,195],"algorithm":[61,159],"(FWNRS)":[65],"work.":[68],"Firstly,":[69],"three":[72],"strategies":[74],"to":[75,102,123,131,142,172],"reduce":[76],"search":[79,88],"range.":[80],"first":[82],"one":[83,108,121],"reducing":[85],"rang":[89],"of":[90,128,176],"each":[91],"testing":[92],"sample":[93],"from":[94,115],"whole":[96],"universe":[97],"or":[98],"boundary":[100],"region":[101,113],"corresponding":[104,117],"neighborhood.":[105,118],"second":[107],"removing":[110],"positive":[112],"samples":[114],"third":[120],"initial":[126],"value":[127,137],"cycle":[130],"be":[132,143],"greater":[133],"than":[134,187],"final":[136],"and":[138],"step":[140],"size":[141],"negative":[144],"when":[145],"radius":[148],"\u03b4":[149],"optimizing.":[151],"Secondly,":[152],"design":[154],"strategies.":[164],"Finally,":[165],"six":[166],"UCI":[167],"benchmark":[168],"datasets":[169],"used":[171],"verify":[173],"FWNRS.":[177],"experimental":[179],"results":[180],"illustrate":[181],"FWNRS":[183],"more":[185],"efficient":[186],"state-of-the-art":[189],"comparison":[190],"algorithms,":[191],"algorithms.":[198]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
