{"id":"https://openalex.org/W2166739810","doi":"https://doi.org/10.1109/ijcnn.2008.4633966","title":"Multi-label imbalanced data enrichment process in neural net classifier training","display_name":"Multi-label imbalanced data enrichment process in neural net classifier training","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2166739810","doi":"https://doi.org/10.1109/ijcnn.2008.4633966","mag":"2166739810"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2008.4633966","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4633966","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","raw_type":"proceedings-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/A5081407706","display_name":"Gorn Tepvorachai","orcid":null},"institutions":[{"id":"https://openalex.org/I58956616","display_name":"Case Western Reserve University","ror":"https://ror.org/051fd9666","country_code":"US","type":"education","lineage":["https://openalex.org/I58956616"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Gorn Tepvorachai","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH, USA","institution_ids":["https://openalex.org/I58956616"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046620750","display_name":"C. Papachristou","orcid":"https://orcid.org/0000-0002-5399-3208"},"institutions":[{"id":"https://openalex.org/I58956616","display_name":"Case Western Reserve University","ror":"https://ror.org/051fd9666","country_code":"US","type":"education","lineage":["https://openalex.org/I58956616"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chris Papachristou","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH, USA","institution_ids":["https://openalex.org/I58956616"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5081407706"],"corresponding_institution_ids":["https://openalex.org/I58956616"],"apc_list":null,"apc_paid":null,"fwci":1.7161,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.88354079,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1301","last_page":"1307"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9970999956130981,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9970999956130981,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9965999722480774,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.991100013256073,"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":0.7710387110710144},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7184468507766724},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.63197922706604},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6217418909072876},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5984201431274414},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5957603454589844},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5288523435592651},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"Multi-label classification","score":0.5131148099899292},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4667739272117615},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4650830626487732},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06103864312171936}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7710387110710144},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7184468507766724},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.63197922706604},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6217418909072876},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5984201431274414},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5957603454589844},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5288523435592651},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.5131148099899292},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4667739272117615},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4650830626487732},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06103864312171936},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2008.4633966","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4633966","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W49844592","https://openalex.org/W1501500081","https://openalex.org/W1514205146","https://openalex.org/W1540210097","https://openalex.org/W1563088657","https://openalex.org/W1591553353","https://openalex.org/W1870097978","https://openalex.org/W1941659294","https://openalex.org/W1969674925","https://openalex.org/W1989149221","https://openalex.org/W1992419399","https://openalex.org/W1998839399","https://openalex.org/W2104167780","https://openalex.org/W2107205693","https://openalex.org/W2124776405","https://openalex.org/W2136804817","https://openalex.org/W2141412684","https://openalex.org/W2145224695","https://openalex.org/W2148143831","https://openalex.org/W2148684197","https://openalex.org/W2156935079","https://openalex.org/W2161898480","https://openalex.org/W2791170912","https://openalex.org/W6602015638","https://openalex.org/W6664464457"],"related_works":["https://openalex.org/W2981877337","https://openalex.org/W3203938600","https://openalex.org/W2169074127","https://openalex.org/W83146503","https://openalex.org/W2163707935","https://openalex.org/W202723009","https://openalex.org/W2145955964","https://openalex.org/W2188612292","https://openalex.org/W2165396616","https://openalex.org/W2058882606"],"abstract_inverted_index":{"Semantic":[0],"scene":[1],"classification,":[2],"robotic":[3,54],"state":[4],"recognition,":[5],"and":[6,41,74],"many":[7],"other":[8],"real-world":[9],"applications":[10],"involve":[11],"multi-label":[12,73],"classification":[13,48],"with":[14,46],"imbalanced":[15,39,75],"data.":[16],"In":[17],"this":[18],"paper,":[19],"we":[20],"address":[21],"these":[22],"problems":[23],"by":[24],"using":[25],"an":[26],"enrichment":[27,34],"process":[28,35],"in":[29,70],"neural":[30,44,67],"net":[31,45,68],"training.":[32],"The":[33],"can":[36],"manage":[37],"the":[38,43,72],"data":[40,76],"train":[42],"high":[47],"accuracy.":[49],"Experimental":[50],"results":[51],"on":[52],"a":[53],"arm":[55],"controller":[56],"show":[57],"that":[58],"our":[59],"method":[60],"has":[61],"better":[62],"generalization":[63],"performance":[64],"than":[65],"traditional":[66],"training":[69],"solving":[71],"problems.":[77]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}