{"id":"https://openalex.org/W4206794339","doi":"https://doi.org/10.1109/bigdata52589.2021.9671291","title":"Hierarchical MultiClass AdaBoost","display_name":"Hierarchical MultiClass AdaBoost","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4206794339","doi":"https://doi.org/10.1109/bigdata52589.2021.9671291"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9671291","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671291","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","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/A5021442429","display_name":"Charalampos Chelmis","orcid":"https://orcid.org/0000-0002-5920-1451"},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Charalampos Chelmis","raw_affiliation_strings":["Department of Computer Science, University at Albany, SUNY, Albany, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University at Albany, SUNY, Albany, New York, USA","institution_ids":["https://openalex.org/I392282"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031483487","display_name":"Wenting Qi","orcid":"https://orcid.org/0000-0002-5931-9855"},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenting Qi","raw_affiliation_strings":["Department of Computer Science, University at Albany, SUNY, Albany, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University at Albany, SUNY, Albany, New York, USA","institution_ids":["https://openalex.org/I392282"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I392282"],"apc_list":null,"apc_paid":null,"fwci":0.7326,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.74665868,"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":"5063","last_page":"5070"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9991000294685364,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9991000294685364,"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":0.9973000288009644,"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":0.9968000054359436,"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/multiclass-classification","display_name":"Multiclass classification","score":0.8015924692153931},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.792061448097229},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7576483488082886},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7460014820098877},{"id":"https://openalex.org/keywords/hierarchy","display_name":"Hierarchy","score":0.7415744066238403},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6921622157096863},{"id":"https://openalex.org/keywords/class-hierarchy","display_name":"Class hierarchy","score":0.49354732036590576},{"id":"https://openalex.org/keywords/simplicity","display_name":"Simplicity","score":0.47385647892951965},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.45991483330726624},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3863430619239807},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.16531607508659363}],"concepts":[{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.8015924692153931},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.792061448097229},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7576483488082886},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7460014820098877},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.7415744066238403},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6921622157096863},{"id":"https://openalex.org/C2781289151","wikidata":"https://www.wikidata.org/wiki/Q2903989","display_name":"Class hierarchy","level":3,"score":0.49354732036590576},{"id":"https://openalex.org/C2776372474","wikidata":"https://www.wikidata.org/wiki/Q508291","display_name":"Simplicity","level":2,"score":0.47385647892951965},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.45991483330726624},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3863430619239807},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.16531607508659363},{"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C34447519","wikidata":"https://www.wikidata.org/wiki/Q179522","display_name":"Market economy","level":1,"score":0.0},{"id":"https://openalex.org/C73752529","wikidata":"https://www.wikidata.org/wiki/Q79872","display_name":"Object-oriented programming","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata52589.2021.9671291","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671291","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W55768394","https://openalex.org/W85880394","https://openalex.org/W146125889","https://openalex.org/W1588401315","https://openalex.org/W1594868493","https://openalex.org/W1643574276","https://openalex.org/W1967542092","https://openalex.org/W1968969471","https://openalex.org/W1988790447","https://openalex.org/W1988841006","https://openalex.org/W1993387039","https://openalex.org/W2008835805","https://openalex.org/W2014566476","https://openalex.org/W2024046085","https://openalex.org/W2030848407","https://openalex.org/W2073040595","https://openalex.org/W2084319893","https://openalex.org/W2091961126","https://openalex.org/W2100805904","https://openalex.org/W2111979819","https://openalex.org/W2114315281","https://openalex.org/W2123096872","https://openalex.org/W2129018774","https://openalex.org/W2135140174","https://openalex.org/W2135293965","https://openalex.org/W2142399242","https://openalex.org/W2145073242","https://openalex.org/W2150102617","https://openalex.org/W2150766729","https://openalex.org/W2165853036","https://openalex.org/W2169863116","https://openalex.org/W2171066191","https://openalex.org/W2407666710","https://openalex.org/W2759474451","https://openalex.org/W2803270043","https://openalex.org/W3015740509","https://openalex.org/W4212883601","https://openalex.org/W4243874760","https://openalex.org/W4244952642","https://openalex.org/W6603408101","https://openalex.org/W6605953338","https://openalex.org/W6635310694","https://openalex.org/W6680273311","https://openalex.org/W6681651645","https://openalex.org/W6681875376","https://openalex.org/W6713755453","https://openalex.org/W6752122265"],"related_works":["https://openalex.org/W2079027950","https://openalex.org/W2357813254","https://openalex.org/W2024223694","https://openalex.org/W2622979832","https://openalex.org/W1971029554","https://openalex.org/W4388185001","https://openalex.org/W2051901529","https://openalex.org/W4229654425","https://openalex.org/W1522999595","https://openalex.org/W1541135463"],"abstract_inverted_index":{"One":[0],"of":[1,12,32,94],"the":[2,33,45,70,84,92,95],"most":[3],"challenging":[4],"machine":[5],"learning":[6,53],"problems":[7],"is":[8],"a":[9,30,64],"particular":[10],"case":[11],"classification":[13,61],"in":[14,29,50,97],"which":[15],"classes":[16],"are":[17],"hierarchically":[18],"structured":[19],"and":[20],"data":[21],"instances":[22],"can":[23],"be":[24,56],"assigned":[25],"multiple":[26],"labels":[27],"residing":[28],"path":[31],"hierarchy.":[34],"In":[35],"this":[36],"paper,":[37],"we":[38],"propose":[39],"hierarchy\u2013aware":[40,65],"multiclass":[41,60,99],"AdaBoost,":[42],"allowing":[43],"for":[44,58],"first":[46],"time":[47],"weak":[48],"classifiers":[49],"an":[51],"ensemble":[52],"setting":[54],"to":[55],"trained":[57],"hierarchical":[59,98],"while":[62],"incorporating":[63],"loss":[66],"function":[67],"directly":[68],"into":[69],"training":[71],"process.":[72],"Experimental":[73],"results":[74],"on":[75],"numerous":[76],"real\u2013world":[77],"datasets":[78],"show":[79],"that,":[80],"despite":[81],"its":[82],"simplicity,":[83],"proposed":[85],"algorithm":[86],"outperforms":[87],"all":[88],"baselines,":[89],"arising":[90],"as":[91],"state":[93],"art":[96],"classification.":[100]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}