{"id":"https://openalex.org/W3004393413","doi":"https://doi.org/10.1109/ieem44572.2019.8978791","title":"On Fusing Multiple Instance Selection Results","display_name":"On Fusing Multiple Instance Selection Results","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3004393413","doi":"https://doi.org/10.1109/ieem44572.2019.8978791","mag":"3004393413"},"language":"en","primary_location":{"id":"doi:10.1109/ieem44572.2019.8978791","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem44572.2019.8978791","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","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/A5045234607","display_name":"Chih\u2010Fong Tsai","orcid":"https://orcid.org/0000-0002-5991-2253"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"C.-F. Tsai","raw_affiliation_strings":["Department of Information Management, National Central University, Taoyuan, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Management, National Central University, Taoyuan, Taiwan","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055777557","display_name":"Ya\u2010Han Hu","orcid":"https://orcid.org/0000-0002-3285-2983"},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Y.-H. Hu","raw_affiliation_strings":["Department of Information Management, National Chung Cheng University, Chiayi, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Management, National Chung Cheng University, Chiayi, Taiwan","institution_ids":["https://openalex.org/I148099254"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112503787","display_name":"Ming-Tsung Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"M.-C. Wang","raw_affiliation_strings":["Department of Business Administration, National Chung Cheng University, Chiayi, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Business Administration, National Chung Cheng University, Chiayi, Taiwan","institution_ids":["https://openalex.org/I148099254"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110197354","display_name":"Koting Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"K.E. Liu","raw_affiliation_strings":["Department of Agricultural Economics, National Taiwan University, Taipei, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Agricultural Economics, National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":"6","issue":null,"first_page":"1546","last_page":"1549"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9997000098228455,"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":0.9997000098228455,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9803000092506409,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9789000153541565,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6598192453384399},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.641958475112915},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6371785402297974},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6318485736846924},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.576797366142273},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.520871639251709},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.4884699881076813},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.46218904852867126},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.435366690158844},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4112812876701355},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35235804319381714},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0777231752872467}],"concepts":[{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6598192453384399},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.641958475112915},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6371785402297974},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6318485736846924},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.576797366142273},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.520871639251709},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.4884699881076813},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.46218904852867126},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.435366690158844},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4112812876701355},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35235804319381714},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0777231752872467},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieem44572.2019.8978791","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem44572.2019.8978791","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1530010412","https://openalex.org/W2066883679","https://openalex.org/W2122496402","https://openalex.org/W2123623606","https://openalex.org/W2135547590","https://openalex.org/W2147169507","https://openalex.org/W2151537585","https://openalex.org/W2158449659","https://openalex.org/W2168690758","https://openalex.org/W4244238212"],"related_works":["https://openalex.org/W2989490741","https://openalex.org/W3092506759","https://openalex.org/W2367545121","https://openalex.org/W4248881655","https://openalex.org/W2482165163","https://openalex.org/W3010890513","https://openalex.org/W120741642","https://openalex.org/W138569904","https://openalex.org/W2390914021","https://openalex.org/W2389417819"],"abstract_inverted_index":{"Instance":[0],"selection":[1,40,60,68,78],"is":[2,12,138],"an":[3],"important":[4],"preprocessing":[5],"step":[6],"in":[7,45],"data":[8,17],"mining.":[9],"Its":[10],"aim":[11],"to":[13,28,56],"filter":[14],"out":[15],"unrepresentative":[16],"samples":[18],"from":[19],"a":[20],"given":[21],"training":[22],"dataset,":[23],"which":[24,70],"allow":[25],"the":[26,32,46,52,83,101,108,115,120,132,139],"classifier":[27],"perform":[29],"better":[30,140],"than":[31],"one":[33],"without":[34],"instance":[35,39,59,67],"selection.":[36],"Since":[37],"various":[38,95],"algorithms":[41],"have":[42],"been":[43],"proposed":[44],"literature,":[47],"no":[48],"study":[49],"considers":[50],"applying":[51],"information":[53],"fusion":[54],"principle":[55],"combine":[57],"multiple":[58],"results.":[61],"This":[62],"paper":[63],"uses":[64],"three":[65],"well-known":[66],"algorithms,":[69],"are":[71,80,130],"IB3,":[72],"DROP3,":[73],"and":[74,76,86,105,127,136],"GA,":[75],"their":[77],"results":[79,91],"combined":[81],"via":[82],"union,":[84],"intersection,":[85],"multi-intersection":[87],"strategies.":[88],"Our":[89],"experimental":[90],"based":[92],"on":[93],"50":[94],"domains":[96],"of":[97],"datasets":[98],"show":[99],"that":[100],"union":[102,133],"between":[103,134],"GA":[104],"DROP3":[106,135],"performs":[107],"best.":[109],"However,":[110],"it":[111],"does":[112],"not":[113],"produce":[114],"largest":[116],"reduction":[117,128],"rate.":[118],"On":[119],"other":[121],"hand,":[122],"if":[123],"both":[124],"classification":[125],"accuracy":[126],"rate":[129],"considered,":[131],"IB3":[137],"choice.":[141]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}