{"id":"https://openalex.org/W2011412734","doi":"https://doi.org/10.1142/s0218001496000530","title":"COMPARISON OF VARIOUS ROUTINES FOR UNKNOWN ATTRIBUTE VALUE PROCESSING: THE COVERING PARADIGM","display_name":"COMPARISON OF VARIOUS ROUTINES FOR UNKNOWN ATTRIBUTE VALUE PROCESSING: THE COVERING PARADIGM","publication_year":1996,"publication_date":"1996-12-01","ids":{"openalex":"https://openalex.org/W2011412734","doi":"https://doi.org/10.1142/s0218001496000530","mag":"2011412734"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001496000530","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001496000530","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","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/A5037727151","display_name":"Ivan Br\u016fha","orcid":null},"institutions":[{"id":"https://openalex.org/I98251732","display_name":"McMaster University","ror":"https://ror.org/02fa3aq29","country_code":"CA","type":"education","lineage":["https://openalex.org/I98251732"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"IVAN BRUHA","raw_affiliation_strings":["Department of Computer Science and Systems, McMaster University, Hamilton, Ontario, Canada L8S4K1, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Systems, McMaster University, Hamilton, Ontario, Canada L8S4K1, Canada","institution_ids":["https://openalex.org/I98251732"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025523396","display_name":"Franti\u0161ek Fran\u011bk","orcid":"https://orcid.org/0000-0002-4110-2113"},"institutions":[{"id":"https://openalex.org/I98251732","display_name":"McMaster University","ror":"https://ror.org/02fa3aq29","country_code":"CA","type":"education","lineage":["https://openalex.org/I98251732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"FRANTISEK FRANEK","raw_affiliation_strings":["Department of Computer Science and Systems, McMaster University, Hamilton, Ontario, Canada L8S4K1, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Systems, McMaster University, Hamilton, Ontario, Canada L8S4K1, Canada","institution_ids":["https://openalex.org/I98251732"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5037727151"],"corresponding_institution_ids":["https://openalex.org/I98251732"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.20297174,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"10","issue":"08","first_page":"939","last_page":"955"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9991999864578247,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9904000163078308,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9876000285148621,"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/computer-science","display_name":"Computer science","score":0.6812218427658081},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6486091613769531},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.6013171672821045},{"id":"https://openalex.org/keywords/extension","display_name":"Extension (predicate logic)","score":0.5908942222595215},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5634284019470215},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.48155477643013},{"id":"https://openalex.org/keywords/variable-and-attribute","display_name":"Variable and attribute","score":0.4263794422149658},{"id":"https://openalex.org/keywords/attribute-domain","display_name":"Attribute domain","score":0.42203980684280396},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40888214111328125},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3859429359436035},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1941913366317749},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.06856176257133484}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6812218427658081},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6486091613769531},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.6013171672821045},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.5908942222595215},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5634284019470215},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.48155477643013},{"id":"https://openalex.org/C12692103","wikidata":"https://www.wikidata.org/wiki/Q113312","display_name":"Variable and attribute","level":4,"score":0.4263794422149658},{"id":"https://openalex.org/C75814411","wikidata":"https://www.wikidata.org/wiki/Q4818714","display_name":"Attribute domain","level":3,"score":0.42203980684280396},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40888214111328125},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3859429359436035},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1941913366317749},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.06856176257133484},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001496000530","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001496000530","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W22857217","https://openalex.org/W177590838","https://openalex.org/W203696055","https://openalex.org/W1493704672","https://openalex.org/W1588684274","https://openalex.org/W1927345150","https://openalex.org/W1997082363","https://openalex.org/W2075038844","https://openalex.org/W2125055259","https://openalex.org/W2136000097","https://openalex.org/W2149706766","https://openalex.org/W2485672621"],"related_works":["https://openalex.org/W2362911251","https://openalex.org/W2003220380","https://openalex.org/W2355009088","https://openalex.org/W2343536755","https://openalex.org/W2361652241","https://openalex.org/W2490482458","https://openalex.org/W2884866368","https://openalex.org/W2357538651","https://openalex.org/W1985171608","https://openalex.org/W2382857162"],"abstract_inverted_index":{"Simple":[0],"inductive":[1],"learning":[2,56,131],"algorithms":[3,66],"assume":[4],"that":[5,49,105],"all":[6,159],"attribute":[7,26,47,90,108,147],"values":[8,27,48,148],"are":[9,154,162],"available.":[10],"The":[11,92,110,121,138],"well-known":[12,63],"Quinlan's":[13],"paper":[14,38],"1":[15],"discusses":[16],"quite":[17],"a":[18,58],"few":[19],"routines":[20,41,95,161],"for":[21,42,53,85,130],"the":[22,29,43,54,62,78,86,119],"processing":[23,44,87,126],"of":[24,35,45,61,72,88,99,112,123,140,145,158],"unknown":[25,46,89,107,124,146],"in":[28,97,116,118,135],"TDIDT":[30],"family":[31],"and":[32,68,132,156],"analyzes":[33],"seven":[34],"them.":[36],"This":[37],"introduces":[39],"five":[40,94,160],"have":[50],"been":[51],"designed":[52],"CN4":[55,69],"algorithm,":[57],"large":[59],"extension":[60],"CN2.":[64],"Both":[65],"CN2":[67,81],"induce":[70],"lists":[71],"decision":[73],"rules":[74],"from":[75],"examples":[76,103],"applying":[77],"covering":[79],"paradigm.":[80],"offers":[82],"two":[83],"ways":[84],"values.":[91,109],"CN4's":[93],"differ":[96],"style":[98],"matching":[100,113],"complexes":[101],"with":[102,142],"(objects)":[104],"involve":[106],"definition":[111],"is":[114,127],"discussed":[115],"detail":[117],"paper.":[120],"strategy":[122],"value":[125],"described":[128],"both":[129],"classification":[133],"phases":[134],"individual":[136],"routines.":[137],"results":[139],"experiments":[141],"various":[143],"percentages":[144],"on":[149],"real-world":[150],"(mostly":[151],"medical)":[152],"data":[153],"presented":[155],"performances":[157],"compared.":[163]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}