{"id":"https://openalex.org/W4396852936","doi":"https://doi.org/10.1109/access.2024.3400693","title":"A Flat-Hierarchical Approach Based on Machine Learning Model for e-Commerce Product Classification","display_name":"A Flat-Hierarchical Approach Based on Machine Learning Model for e-Commerce Product Classification","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4396852936","doi":"https://doi.org/10.1109/access.2024.3400693"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3400693","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2024.3400693","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10530036.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10530036.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5094332286","display_name":"Harold Enrique Cotacallapa Mamani","orcid":"https://orcid.org/0000-0002-3164-1682"},"institutions":[{"id":"https://openalex.org/I4210140760","display_name":"Universidad Peruana Uni\u00f3n","ror":"https://ror.org/042gckq23","country_code":"PE","type":"education","lineage":["https://openalex.org/I4210140760"]}],"countries":["PE"],"is_corresponding":true,"raw_author_name":"Harold Cotacallapa","raw_affiliation_strings":["Facultad de Ingeniería y Arquitectura, Universidad Peruana Unión, Lima, Peru"],"raw_orcid":"https://orcid.org/0000-0002-3164-1682","affiliations":[{"raw_affiliation_string":"Facultad de Ingeniería y Arquitectura, Universidad Peruana Unión, Lima, Peru","institution_ids":["https://openalex.org/I4210140760"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036120313","display_name":"Nem\u00edas Saboya","orcid":"https://orcid.org/0000-0002-7166-2197"},"institutions":[{"id":"https://openalex.org/I4210140760","display_name":"Universidad Peruana Uni\u00f3n","ror":"https://ror.org/042gckq23","country_code":"PE","type":"education","lineage":["https://openalex.org/I4210140760"]}],"countries":["PE"],"is_corresponding":false,"raw_author_name":"Nemias Saboya","raw_affiliation_strings":["Facultad de Ingeniería y Arquitectura, Universidad Peruana Unión, Lima, Peru"],"raw_orcid":"https://orcid.org/0000-0002-7166-2197","affiliations":[{"raw_affiliation_string":"Facultad de Ingeniería y Arquitectura, Universidad Peruana Unión, Lima, Peru","institution_ids":["https://openalex.org/I4210140760"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024974930","display_name":"Paulo Canas Rodrigues","orcid":"https://orcid.org/0000-0002-1248-9910"},"institutions":[{"id":"https://openalex.org/I126158947","display_name":"Universidade Federal da Bahia","ror":"https://ror.org/03k3p7647","country_code":"BR","type":"education","lineage":["https://openalex.org/I126158947"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Paulo Canas Rodrigues","raw_affiliation_strings":["Department of Statistics, Federal University of Bahia, Salvador, Brazil"],"raw_orcid":"https://orcid.org/0000-0002-1248-9910","affiliations":[{"raw_affiliation_string":"Department of Statistics, Federal University of Bahia, Salvador, Brazil","institution_ids":["https://openalex.org/I126158947"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088560375","display_name":"Rodrigo Salas","orcid":"https://orcid.org/0000-0002-0350-6811"},"institutions":[{"id":"https://openalex.org/I79274474","display_name":"University of Valpara\u00edso","ror":"https://ror.org/00h9jrb69","country_code":"CL","type":"education","lineage":["https://openalex.org/I79274474"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Rodrigo Salas","raw_affiliation_strings":["Escuela de Ingeniería C. Biomédica, Universidad de Valparaíso, Valparaiso, Chile"],"raw_orcid":"https://orcid.org/0000-0002-0350-6811","affiliations":[{"raw_affiliation_string":"Escuela de Ingeniería C. Biomédica, Universidad de Valparaíso, Valparaiso, Chile","institution_ids":["https://openalex.org/I79274474"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030048049","display_name":"Javier Linkolk L\u00f3pez\u2010Gonzales","orcid":"https://orcid.org/0000-0003-0847-0552"},"institutions":[{"id":"https://openalex.org/I4210140760","display_name":"Universidad Peruana Uni\u00f3n","ror":"https://ror.org/042gckq23","country_code":"PE","type":"education","lineage":["https://openalex.org/I4210140760"]}],"countries":["PE"],"is_corresponding":false,"raw_author_name":"Javier Linkolk L\u00f3pez-Gonzales","raw_affiliation_strings":["Escuela de Posgrado, Universidad Peruana Unión, Lima, Peru"],"raw_orcid":"https://orcid.org/0000-0003-0847-0552","affiliations":[{"raw_affiliation_string":"Escuela de Posgrado, Universidad Peruana Unión, Lima, Peru","institution_ids":["https://openalex.org/I4210140760"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5094332286"],"corresponding_institution_ids":["https://openalex.org/I4210140760"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.627,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.85487713,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"12","issue":null,"first_page":"72730","last_page":"72745"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9979000091552734,"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":0.9979000091552734,"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":0.9968000054359436,"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"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9962000250816345,"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":0.7562083005905151},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7429273128509521},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7013784050941467},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6281329989433289},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.6161667704582214},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5131062269210815},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4652498662471771},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.45414233207702637}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7562083005905151},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7429273128509521},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7013784050941467},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6281329989433289},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.6161667704582214},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5131062269210815},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4652498662471771},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.45414233207702637}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3400693","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2024.3400693","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10530036.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:64fdddbd54ee43ac81a7b740e2416ba9","is_oa":true,"landing_page_url":"https://doaj.org/article/64fdddbd54ee43ac81a7b740e2416ba9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 72730-72745 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3400693","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2024.3400693","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10530036.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4699999988079071,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[{"id":"https://openalex.org/G5936009186","display_name":null,"funder_award_id":"ICN2021_004","funder_id":"https://openalex.org/F4320331146","funder_display_name":"Agencia Nacional de Investigaci\u00f3n y Desarrollo"},{"id":"https://openalex.org/G5964718519","display_name":null,"funder_award_id":"1221938","funder_id":"https://openalex.org/F4320338073","funder_display_name":"Fondo Nacional de Desarrollo Cient\u00edfico y Tecnol\u00f3gico"}],"funders":[{"id":"https://openalex.org/F4320331146","display_name":"Agencia Nacional de Investigaci\u00f3n y Desarrollo","ror":null},{"id":"https://openalex.org/F4320338073","display_name":"Fondo Nacional de Desarrollo Cient\u00edfico y Tecnol\u00f3gico","ror":"https://ror.org/02ap3w078"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4396852936.pdf"},"referenced_works_count":67,"referenced_works":["https://openalex.org/W1930624869","https://openalex.org/W2038906069","https://openalex.org/W2118585731","https://openalex.org/W2149298154","https://openalex.org/W2150579376","https://openalex.org/W2150766729","https://openalex.org/W2166183437","https://openalex.org/W2293569829","https://openalex.org/W2295598076","https://openalex.org/W2493916176","https://openalex.org/W2510938745","https://openalex.org/W2584417445","https://openalex.org/W2613786420","https://openalex.org/W2619948196","https://openalex.org/W2741511332","https://openalex.org/W2766360596","https://openalex.org/W2789758093","https://openalex.org/W2892166671","https://openalex.org/W2894747149","https://openalex.org/W2904818199","https://openalex.org/W2911964244","https://openalex.org/W2950510531","https://openalex.org/W2963626623","https://openalex.org/W2969896787","https://openalex.org/W2989514282","https://openalex.org/W2997591727","https://openalex.org/W3013782982","https://openalex.org/W3043681474","https://openalex.org/W3044445863","https://openalex.org/W3046043543","https://openalex.org/W3046054871","https://openalex.org/W3049632937","https://openalex.org/W3133746906","https://openalex.org/W3161934949","https://openalex.org/W3162849074","https://openalex.org/W3175170601","https://openalex.org/W3187798969","https://openalex.org/W3191404950","https://openalex.org/W4212926655","https://openalex.org/W4224262247","https://openalex.org/W4249164878","https://openalex.org/W4281642792","https://openalex.org/W4288547960","https://openalex.org/W4312467257","https://openalex.org/W4313345715","https://openalex.org/W4324333799","https://openalex.org/W4361008937","https://openalex.org/W4362579746","https://openalex.org/W6677656871","https://openalex.org/W6680244274","https://openalex.org/W6719382505","https://openalex.org/W6732909215","https://openalex.org/W6753328955","https://openalex.org/W6759821805","https://openalex.org/W6760075799","https://openalex.org/W6760257190","https://openalex.org/W6760299454","https://openalex.org/W6760355895","https://openalex.org/W6767166871","https://openalex.org/W6782151383","https://openalex.org/W6784777585","https://openalex.org/W6784821773","https://openalex.org/W6786558520","https://openalex.org/W6786963736","https://openalex.org/W6788441589","https://openalex.org/W6799432573","https://openalex.org/W7019139687"],"related_works":["https://openalex.org/W4396689146","https://openalex.org/W4200112873","https://openalex.org/W4406918474","https://openalex.org/W4367336074","https://openalex.org/W2955796858","https://openalex.org/W3154045278","https://openalex.org/W4379620016","https://openalex.org/W4393666307","https://openalex.org/W3210764983","https://openalex.org/W4393443811"],"abstract_inverted_index":{"Within":[0],"the":[1,5,70,169,178,192,200,216,221,226],"e-commerce":[2,117],"sphere,":[3],"optimizing":[4],"product":[6,91,111],"classification":[7,92,105],"process":[8],"assumes":[9],"pivotal":[10],"importance,":[11],"owing":[12],"to":[13,199],"its":[14],"direct":[15],"influence":[16],"on":[17,94],"operational":[18],"efficiency":[19],"and":[20,102,150,176,214,230],"profitability.":[21],"In":[22,122],"this":[23,38,125,196,237],"context,":[24],"employing":[25],"machine":[26,132],"learning":[27,133],"algorithms":[28],"stands":[29],"out":[30],"as":[31,189],"a":[32,48,87,95,108,115,127,164,205],"premier":[33],"solution":[34,88],"for":[35,89,220,233],"effectively":[36],"automating":[37],"process.":[39],"The":[40,61],"design":[41],"of":[42,56,124,130],"these":[43],"models":[44,162],"commonly":[45],"adopts":[46],"either":[47],"flat":[49,71,101,171],"or":[50],"local":[51,103,180],"(hierarchical)":[52,104],"approach.":[53,166],"However,":[54],"each":[55],"them":[57],"exhibits":[58],"significant":[59,206],"limitations.":[60],"regional":[62],"approach":[63,72,157,172,181],"introduces":[64,86],"taxonomic":[65],"inconsistencies":[66],"in":[67,119,236],"predictions,":[68],"whereas":[69],"becomes":[73],"inefficient":[74],"when":[75],"dealing":[76],"with":[77],"extensive":[78],"datasets":[79],"featuring":[80],"high":[81],"granularity.":[82],"Therefore,":[83],"our":[84],"research":[85],"hierarchical":[90],"based":[93],"Machine":[96],"Learning":[97],"model":[98,158,173,186],"that":[99],"integrates":[100],"approaches":[106],"using":[107,163],"4-level":[109],"electronic":[110],"dataset":[112,208],"obtained":[113],"from":[114],"renowned":[116],"platform":[118],"Latin":[120],"America.":[121],"pursuit":[123],"goal,":[126],"comparative":[128],"analysis":[129],"seven":[131],"algorithms,":[134],"including":[135],"Multinomial":[136,143],"Naive":[137],"Bayes,":[138],"Linear":[139],"Support":[140],"Vector":[141],"Classifier,":[142],"Logistic":[144],"Regression,":[145],"Random":[146],"Forest,":[147],"XGBoost,":[148],"FastText,":[149],"Voting":[151],"Ensemble,":[152],"was":[153],"conducted.":[154],"This":[155],"hybrid":[156],"performs":[159],"better":[160],"than":[161],"single":[165],"It":[167,223],"surpassed":[168],"top-performing":[170],"by":[174,187,191,203],"0.15%":[175],"outperformed":[177],"leading":[179],"(Local":[182],"Classifier":[183],"per":[184],"Level)":[185],"4.88%,":[188],"measured":[190],"weighted":[193],"F1-score.":[194],"Additionally,":[195],"paper":[197],"contributes":[198],"academic":[201],"community":[202],"presenting":[204],"Spanish-language":[207],"comprising":[209],"over":[210],"one":[211],"million":[212],"products":[213],"discussing":[215],"preprocessing":[217],"techniques":[218],"tailored":[219],"dataset.":[222],"also":[224],"addresses":[225],"study\u2019s":[227],"inherent":[228],"limitations":[229],"potential":[231],"avenues":[232],"future":[234],"exploration":[235],"field.":[238]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}