{"id":"https://openalex.org/W4309214450","doi":"https://doi.org/10.3390/jtaer17040076","title":"AutoML Approach to Stock Keeping Units Segmentation","display_name":"AutoML Approach to Stock Keeping Units Segmentation","publication_year":2022,"publication_date":"2022-11-15","ids":{"openalex":"https://openalex.org/W4309214450","doi":"https://doi.org/10.3390/jtaer17040076"},"language":"en","primary_location":{"id":"doi:10.3390/jtaer17040076","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jtaer17040076","pdf_url":"https://www.mdpi.com/0718-1876/17/4/76/pdf?version=1668485403","source":{"id":"https://openalex.org/S27967161","display_name":"Journal of theoretical and applied electronic commerce research","issn_l":"0718-1876","issn":["0718-1876"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Theoretical and Applied Electronic Commerce Research","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/0718-1876/17/4/76/pdf?version=1668485403","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035485597","display_name":"Ilya Jackson","orcid":"https://orcid.org/0000-0002-7457-6040"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ilya Jackson","raw_affiliation_strings":["Center for Transportation & Logistics, Massachusetts Institute of Technology, 1 Amherst Street, Cambridge, MA 02142, USA"],"raw_orcid":"https://orcid.org/0000-0002-7457-6040","affiliations":[{"raw_affiliation_string":"Center for Transportation & Logistics, Massachusetts Institute of Technology, 1 Amherst Street, Cambridge, MA 02142, USA","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5035485597"],"corresponding_institution_ids":["https://openalex.org/I63966007"],"apc_list":{"value":1000,"currency":"CHF","value_usd":1082},"apc_paid":{"value":1000,"currency":"CHF","value_usd":1082},"fwci":0.4457,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.59566124,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"17","issue":"4","first_page":"1512","last_page":"1528"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9706000089645386,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9593999981880188,"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":0.7025291919708252},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6889104843139648},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5896679162979126},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4941869080066681},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.45766666531562805},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.4351988434791565},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3613854646682739},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3265482187271118},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11821407079696655}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7025291919708252},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6889104843139648},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5896679162979126},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4941869080066681},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.45766666531562805},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.4351988434791565},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3613854646682739},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3265482187271118},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11821407079696655},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/jtaer17040076","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jtaer17040076","pdf_url":"https://www.mdpi.com/0718-1876/17/4/76/pdf?version=1668485403","source":{"id":"https://openalex.org/S27967161","display_name":"Journal of theoretical and applied electronic commerce research","issn_l":"0718-1876","issn":["0718-1876"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Theoretical and Applied Electronic Commerce Research","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:cf73fc09bff34f52836ba941cba08236","is_oa":true,"landing_page_url":"https://doaj.org/article/cf73fc09bff34f52836ba941cba08236","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":"Journal of Theoretical and Applied Electronic Commerce Research, Vol 17, Iss 4, Pp 1512-1528 (2022)","raw_type":"article"},{"id":"pmh:oai:dspace.mit.edu:1721.1/146617","is_oa":true,"landing_page_url":"https://hdl.handle.net/1721.1/146617","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Multidisciplinary Digital Publishing Institute","raw_type":"http://purl.org/eprint/type/JournalArticle"},{"id":"pmh:oai:mdpi.com:/0718-1876/17/4/76/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/jtaer17040076","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Theoretical and Applied Electronic Commerce Research; Volume 17; Issue 4; Pages: 1512-1528","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/jtaer17040076","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jtaer17040076","pdf_url":"https://www.mdpi.com/0718-1876/17/4/76/pdf?version=1668485403","source":{"id":"https://openalex.org/S27967161","display_name":"Journal of theoretical and applied electronic commerce research","issn_l":"0718-1876","issn":["0718-1876"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Theoretical and Applied Electronic Commerce Research","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5099999904632568,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4309214450.pdf"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W1585610988","https://openalex.org/W1728842521","https://openalex.org/W1968316967","https://openalex.org/W1970432968","https://openalex.org/W1973969198","https://openalex.org/W1974209792","https://openalex.org/W1979329931","https://openalex.org/W1987971958","https://openalex.org/W2026360870","https://openalex.org/W2039509714","https://openalex.org/W2060765502","https://openalex.org/W2067191022","https://openalex.org/W2083955576","https://openalex.org/W2086197761","https://openalex.org/W2087668167","https://openalex.org/W2097998348","https://openalex.org/W2101234009","https://openalex.org/W2131850886","https://openalex.org/W2139047213","https://openalex.org/W2142838865","https://openalex.org/W2151554678","https://openalex.org/W2193209126","https://openalex.org/W2234763457","https://openalex.org/W2342249984","https://openalex.org/W2346419948","https://openalex.org/W2507473779","https://openalex.org/W2515386411","https://openalex.org/W2525726844","https://openalex.org/W2765741717","https://openalex.org/W2771169143","https://openalex.org/W2801150743","https://openalex.org/W2912198671","https://openalex.org/W2922311340","https://openalex.org/W3003257820","https://openalex.org/W3013372977","https://openalex.org/W3080833062","https://openalex.org/W3100857237","https://openalex.org/W3150635270","https://openalex.org/W3165666764","https://openalex.org/W3204904569","https://openalex.org/W4205533987","https://openalex.org/W4205737464","https://openalex.org/W4226100251","https://openalex.org/W4231080135","https://openalex.org/W4280506932","https://openalex.org/W4285287814","https://openalex.org/W4288849041","https://openalex.org/W6660318719","https://openalex.org/W6674385629","https://openalex.org/W6675354045","https://openalex.org/W6796185174"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4224009465","https://openalex.org/W4286629047","https://openalex.org/W79970639","https://openalex.org/W4306321456","https://openalex.org/W4285260836","https://openalex.org/W3046775127","https://openalex.org/W3014300295","https://openalex.org/W1997217298"],"abstract_inverted_index":{"A":[0],"typical":[1],"retailer":[2],"carries":[3],"10,000":[4],"stock-keeping":[5],"units":[6],"(SKUs).":[7],"However,":[8],"these":[9],"numbers":[10],"may":[11,91],"exceed":[12],"hundreds":[13],"of":[14,42,52,71,85,120,146,168],"millions":[15],"for":[16,73,115,125,139],"giants":[17],"such":[18],"as":[19],"Walmart":[20],"and":[21,49,87,95,136,157],"Amazon.":[22],"Besides":[23],"the":[24,40,46,50,69,83,103,116,147,166,176],"volume,":[25],"SKU":[26,74,127],"data":[27,47,174],"can":[28,36],"also":[29],"be":[30,37,92],"high-dimensional,":[31],"which":[32,90],"means":[33],"that":[34,110,172],"SKUs":[35],"segmented":[38],"on":[39,144,165],"basis":[41,167],"various":[43],"attributes.":[44],"Given":[45],"volumes":[48],"multitude":[51],"potentially":[53],"important":[54],"dimensions":[55],"to":[56,62],"consider,":[57],"it":[58],"becomes":[59],"computationally":[60],"impossible":[61],"individually":[63],"manage":[64],"each":[65],"SKU.":[66],"Even":[67],"though":[68],"application":[70],"clustering":[72],"segmentation":[75,128],"is":[76],"common,":[77],"previous":[78],"studies":[79],"do":[80],"not":[81],"address":[82],"problem":[84],"parametrization":[86],"model":[88],"finetuning,":[89],"extremely":[93],"tedious":[94],"time-consuming":[96],"in":[97],"real-world":[98,170],"applications.":[99],"Our":[100],"work":[101],"closes":[102],"research":[104],"gap":[105],"by":[106],"proposing":[107],"a":[108,169],"solution":[109,162],"leverages":[111],"automated":[112,117,126],"machine":[113],"learning":[114],"cluster":[118],"analysis":[119],"SKUs.":[121],"The":[122,160],"proposed":[123,161],"framework":[124],"incorporates":[129],"minibatch":[130],"K-means":[131],"clustering,":[132],"principal":[133],"component":[134],"analysis,":[135],"grid":[137],"search":[138],"parameter":[140],"tuning.":[141],"It":[142],"operates":[143],"top":[145],"Apache":[148],"Parquet":[149],"file":[150],"format,":[151],"an":[152],"efficient,":[153],"structured,":[154],"compressed,":[155],"column-oriented,":[156],"big-data-friendly":[158],"format.":[159],"was":[163],"tested":[164],"dataset":[171],"contained":[173],"at":[175],"pallet":[177],"level.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2025-10-10T00:00:00"}