{"id":"https://openalex.org/W1994729613","doi":"https://doi.org/10.1016/s1088-467x(99)00019-0","title":"Dimensionality optimization by heuristic greedy learning vs. genetic algorithms in knowledge discovery and data mining","display_name":"Dimensionality optimization by heuristic greedy learning vs. genetic algorithms in knowledge discovery and data mining","publication_year":1999,"publication_date":"1999-09-01","ids":{"openalex":"https://openalex.org/W1994729613","doi":"https://doi.org/10.1016/s1088-467x(99)00019-0","mag":"1994729613"},"language":"en","primary_location":{"id":"doi:10.1016/s1088-467x(99)00019-0","is_oa":false,"landing_page_url":"https://doi.org/10.1016/s1088-467x(99)00019-0","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent 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/A5091494821","display_name":"Zhang-Hua Fu","orcid":"https://orcid.org/0000-0002-3740-7408"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Z Fu","raw_affiliation_strings":["Robert H. Smith School of Business, University of Maryland, College Park, MD 20742, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robert H. Smith School of Business, University of Maryland, College Park, MD 20742, USA","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5091494821"],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":0.7921,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.72688419,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"3","issue":"3","first_page":"211","last_page":"225"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9986000061035156,"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"}},{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9986000061035156,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9939000010490417,"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":0.7068518400192261},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.6630786061286926},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.647091805934906},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5900075435638428},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.5453301668167114},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.5147814750671387},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5016739368438721},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4707905352115631},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.46357184648513794},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4357702136039734},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2774582505226135}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7068518400192261},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.6630786061286926},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.647091805934906},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5900075435638428},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.5453301668167114},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.5147814750671387},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5016739368438721},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4707905352115631},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.46357184648513794},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4357702136039734},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2774582505226135},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/s1088-467x(99)00019-0","is_oa":false,"landing_page_url":"https://doi.org/10.1016/s1088-467x(99)00019-0","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W604180349","https://openalex.org/W1497256448","https://openalex.org/W1561348124","https://openalex.org/W1587987385","https://openalex.org/W1601529450","https://openalex.org/W2038171684","https://openalex.org/W2102009083","https://openalex.org/W2117812871","https://openalex.org/W2149706766","https://openalex.org/W2151163048","https://openalex.org/W2159173424","https://openalex.org/W2159573450","https://openalex.org/W3023540311"],"related_works":["https://openalex.org/W1827895227","https://openalex.org/W2357854711","https://openalex.org/W4243448361","https://openalex.org/W4285104409","https://openalex.org/W2054759342","https://openalex.org/W4210317843","https://openalex.org/W2051700896","https://openalex.org/W1552255772","https://openalex.org/W2111524952","https://openalex.org/W4234690372"],"abstract_inverted_index":{"Dimensionality":[0],"optimization":[1,21,168],"involves":[2],"optimizing":[3,206],"the":[4,25,38,54,68,82,87,101,154,174,182,190,196,200,205,221],"size":[5],"of":[6,19,103,125,157,184,199,211,216,223],"data":[7,27,79,92,102,133,160,233],"sets":[8,80,161],"from":[9,162],"both":[10,31,163],"dimensions,":[11],"variable":[12],"and":[13,58,94,148,194,226,232],"observation":[14],"selections.":[15],"The":[16,106,214],"ultimate":[17],"objective":[18],"dimensionality":[20],"is":[22,50,57,71,86,170],"to":[23,98,128,151,203],"obtain":[24],"induced":[26],"space,":[28],"by":[29],"reducing":[30],"dimensionalities":[32],"in":[33,63,74,81,118,173,187],"such":[34,64],"a":[35,65,123,139],"way":[36],"that":[37,84,142],"reduced":[39],"subset":[40,56,70,156],"could":[41],"retain":[42],"sufficient":[43],"information.":[44],"In":[45],"most":[46],"real-world":[47],"applications,":[48],"it":[49,85],"not":[51],"known":[52],"what":[53,59],"best":[55],"should":[60],"be":[61,129],"contained":[62],"subset.":[66],"Selecting":[67],"appropriate":[69],"extremely":[72],"important":[73,191],"effectively":[75],"mining":[76,93,134,234],"over":[77],"large":[78,159],"sense":[83],"only":[88],"source":[89],"for":[90,132,229],"any":[91],"knowledge":[95,230],"discovery":[96,231],"algorithm":[97],"work":[99],"with":[100],"interest":[104],"reliably.":[105],"statistical":[107],"as":[108,110],"well":[109],"artificial":[111],"intelligence":[112],"community":[113],"has":[114],"provided":[115],"good":[116],"methods":[117,147],"this":[119],"domain,":[120],"but":[121],"still":[122],"lot":[124],"improvements":[126],"need":[127],"made,":[130],"especially":[131],"applications.":[135],"This":[136],"paper":[137],"introduces":[138],"heuristic":[140,144],"methodology":[141],"integrates":[143],"greedy":[145],"search":[146],"tree-structured":[149],"SampleC4.5":[150],"efficiently":[152],"find":[153],"optimal":[155],"very":[158],"dimensions":[164],"simultaneously.":[165],"A":[166],"GA-based":[167],"approach":[169],"also":[171,219],"proposed":[172,201],"paper.":[175],"Experimental":[176],"results":[177,215],"are":[178],"presented":[179],"which":[180],"illustrate":[181],"effectiveness":[183],"our":[185,217,224],"approaches":[186,225],"digging":[188],"out":[189,210],"underlying":[192],"patterns,":[193],"indicate":[195],"potential":[197],"advantages":[198],"techniques":[202],"improve":[204],"process":[207],"while":[208],"staying":[209],"misleading":[212],"dilemma.":[213],"experiments":[218],"show":[220],"robustness":[222],"complementary":[227],"characteristics":[228],"tasks.":[235]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
