{"id":"https://openalex.org/W2102023927","doi":"https://doi.org/10.1109/iat.2003.1241122","title":"Learning DNF concepts by constrained clustering of positive instances","display_name":"Learning DNF concepts by constrained clustering of positive instances","publication_year":2004,"publication_date":"2004-03-02","ids":{"openalex":"https://openalex.org/W2102023927","doi":"https://doi.org/10.1109/iat.2003.1241122","mag":"2102023927"},"language":"en","primary_location":{"id":"doi:10.1109/iat.2003.1241122","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iat.2003.1241122","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/WIC International Conference on Intelligent Agent Technology, 2003. IAT 2003.","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/A5101423504","display_name":"Minqiang Li","orcid":"https://orcid.org/0000-0001-7929-3747"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Minqiang","raw_affiliation_strings":["Institute of Systems Engineering, Tianjin University, TJU, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Systems Engineering, Tianjin University, TJU, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100382221","display_name":"Zhi Li","orcid":"https://orcid.org/0000-0001-6268-0679"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Zhi","raw_affiliation_strings":["Management School, Tianjin University, TJU, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Management School, Tianjin University, TJU, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"465","last_page":"468"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9922999739646912,"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"}},"topics":[{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9922999739646912,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9908000230789185,"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/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"}}],"keywords":[{"id":"https://openalex.org/keywords/learnability","display_name":"Learnability","score":0.8367182612419128},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.7390514016151428},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7242646813392639},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6569615602493286},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5885607600212097},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5089268684387207},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48984667658805847},{"id":"https://openalex.org/keywords/constrained-clustering","display_name":"Constrained clustering","score":0.4400347173213959},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4155481457710266},{"id":"https://openalex.org/keywords/disjunctive-normal-form","display_name":"Disjunctive normal form","score":0.4151616394519806},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37409085035324097},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.3736017346382141},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3713735044002533},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3458911180496216},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3392038345336914},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.333312451839447},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.17240384221076965}],"concepts":[{"id":"https://openalex.org/C2777723229","wikidata":"https://www.wikidata.org/wiki/Q4367921","display_name":"Learnability","level":2,"score":0.8367182612419128},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7390514016151428},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7242646813392639},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6569615602493286},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5885607600212097},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5089268684387207},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48984667658805847},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.4400347173213959},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4155481457710266},{"id":"https://openalex.org/C136726353","wikidata":"https://www.wikidata.org/wiki/Q903789","display_name":"Disjunctive normal form","level":2,"score":0.4151616394519806},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37409085035324097},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.3736017346382141},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3713735044002533},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3458911180496216},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3392038345336914},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.333312451839447},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.17240384221076965},{"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/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iat.2003.1241122","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iat.2003.1241122","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/WIC International Conference on Intelligent Agent Technology, 2003. IAT 2003.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1570286060","https://openalex.org/W1671614046","https://openalex.org/W1970608725","https://openalex.org/W1978876071","https://openalex.org/W1994022788","https://openalex.org/W2000495995","https://openalex.org/W2017337590","https://openalex.org/W2084812512","https://openalex.org/W2136000097","https://openalex.org/W3112020351","https://openalex.org/W4234760406","https://openalex.org/W4238389014","https://openalex.org/W6634111069","https://openalex.org/W6671611538"],"related_works":["https://openalex.org/W4238857046","https://openalex.org/W2502635581","https://openalex.org/W2126117927","https://openalex.org/W3146523624","https://openalex.org/W2951567704","https://openalex.org/W4300978037","https://openalex.org/W2998008536","https://openalex.org/W2043842763","https://openalex.org/W4312142847","https://openalex.org/W2969974905"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"define":[4],"the":[5,33,44,67,91,94],"conjunctive":[6,30],"learnability":[7],"of":[8,93],"nominal-attribute":[9],"instances":[10,23,36],"space,":[11],"and":[12,47,70,77,90,99],"set":[13],"up":[14],"a":[15,48],"propositional":[16],"concept":[17],"learning":[18],"paradigm":[19],"by":[20],"clustering":[21,45],"positive":[22],"into":[24],"multiple":[25],"divisions.":[26],"All":[27],"divisions":[28],"are":[29,81,84],"learnable":[31],"against":[32],"total":[34],"negative":[35],"set.":[37],"Similarity":[38],"measuring":[39],"is":[40,56,62,97],"introduced":[41],"to":[42,50,64],"guide":[43],"process,":[46],"procedure":[49,61],"generate":[51],"CNF":[52],"rules":[53],"for":[54],"clusters":[55],"described.":[57],"A":[58],"post":[59],"pruning":[60],"designed":[63],"deal":[65],"with":[66,101],"overfitting":[68],"problem,":[69],"two":[71],"criteria":[72],"as":[73],"minimum":[74,78],"covering":[75],"rate":[76,80],"error":[79],"defined.":[82],"Experiments":[83],"implemented":[85],"on":[86],"several":[87],"data":[88],"sets,":[89],"performance":[92],"proposed":[95],"method":[96],"analyzed":[98],"compared":[100],"existing":[102],"algorithms.":[103]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
