{"id":"https://openalex.org/W3217729039","doi":"https://doi.org/10.1155/2021/2179692","title":"Prediction of Merchandise Sales on E-Commerce Platforms Based on Data Mining and Deep Learning","display_name":"Prediction of Merchandise Sales on E-Commerce Platforms Based on Data Mining and Deep Learning","publication_year":2021,"publication_date":"2021-11-28","ids":{"openalex":"https://openalex.org/W3217729039","doi":"https://doi.org/10.1155/2021/2179692","mag":"3217729039"},"language":"en","primary_location":{"id":"doi:10.1155/2021/2179692","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/2179692","pdf_url":"https://downloads.hindawi.com/journals/sp/2021/2179692.pdf","source":{"id":"https://openalex.org/S166774750","display_name":"Scientific Programming","issn_l":"1058-9244","issn":["1058-9244","1875-919X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Programming","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://downloads.hindawi.com/journals/sp/2021/2179692.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023908699","display_name":"Xiaoting Yin","orcid":"https://orcid.org/0000-0003-3165-9396"},"institutions":[{"id":"https://openalex.org/I3131412887","display_name":"Jiangxi University of Technology","ror":"https://ror.org/05k2j8e48","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131412887"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoting Yin","raw_affiliation_strings":["School of Digital Trade, Jiangxi University of Engineering, Xinyu 338000, China"],"raw_orcid":"https://orcid.org/0000-0003-3165-9396","affiliations":[{"raw_affiliation_string":"School of Digital Trade, Jiangxi University of Engineering, Xinyu 338000, China","institution_ids":["https://openalex.org/I3131412887"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056810995","display_name":"Xiaosha Tao","orcid":null},"institutions":[{"id":"https://openalex.org/I3131412887","display_name":"Jiangxi University of Technology","ror":"https://ror.org/05k2j8e48","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131412887"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaosha Tao","raw_affiliation_strings":["School of Digital Trade, Jiangxi University of Engineering, Xinyu 338000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Digital Trade, Jiangxi University of Engineering, Xinyu 338000, China","institution_ids":["https://openalex.org/I3131412887"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5023908699"],"corresponding_institution_ids":["https://openalex.org/I3131412887"],"apc_list":{"value":1800,"currency":"USD","value_usd":1800},"apc_paid":{"value":1800,"currency":"USD","value_usd":1800},"fwci":1.5517,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.85377663,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"2021","issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14319","display_name":"Currency Recognition and Detection","score":0.9613000154495239,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T14319","display_name":"Currency Recognition and Detection","score":0.9613000154495239,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11891","display_name":"Big Data and Business Intelligence","score":0.9513000249862671,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9506999850273132,"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/adaptability","display_name":"Adaptability","score":0.7868009209632874},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7642977237701416},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.630031168460846},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.5945542454719543},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.534782886505127},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.530292809009552},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5138424038887024},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5118764638900757},{"id":"https://openalex.org/keywords/sales-forecasting","display_name":"Sales forecasting","score":0.5064343214035034},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4535941481590271},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.39651036262512207},{"id":"https://openalex.org/keywords/marketing","display_name":"Marketing","score":0.23303836584091187},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.1180327832698822}],"concepts":[{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.7868009209632874},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7642977237701416},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.630031168460846},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.5945542454719543},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.534782886505127},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.530292809009552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5138424038887024},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5118764638900757},{"id":"https://openalex.org/C2984642479","wikidata":"https://www.wikidata.org/wiki/Q7404320","display_name":"Sales forecasting","level":2,"score":0.5064343214035034},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4535941481590271},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.39651036262512207},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.23303836584091187},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.1180327832698822},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"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/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1155/2021/2179692","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/2179692","pdf_url":"https://downloads.hindawi.com/journals/sp/2021/2179692.pdf","source":{"id":"https://openalex.org/S166774750","display_name":"Scientific Programming","issn_l":"1058-9244","issn":["1058-9244","1875-919X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Programming","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b4e3c3abef2748f990b1494ac3fba694","is_oa":true,"landing_page_url":"https://doaj.org/article/b4e3c3abef2748f990b1494ac3fba694","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":"Scientific Programming, Vol 2021 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2021/2179692","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/2179692","pdf_url":"https://downloads.hindawi.com/journals/sp/2021/2179692.pdf","source":{"id":"https://openalex.org/S166774750","display_name":"Scientific Programming","issn_l":"1058-9244","issn":["1058-9244","1875-919X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Programming","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3217729039.pdf","grobid_xml":"https://content.openalex.org/works/W3217729039.grobid-xml"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W2053757129","https://openalex.org/W2075948878","https://openalex.org/W2112796928","https://openalex.org/W2123045220","https://openalex.org/W2138857742","https://openalex.org/W2145094598","https://openalex.org/W2163605009","https://openalex.org/W2618530766","https://openalex.org/W2947517803","https://openalex.org/W2997574889","https://openalex.org/W3005178926","https://openalex.org/W3159659552","https://openalex.org/W3160054584","https://openalex.org/W3198215288","https://openalex.org/W4231109964"],"related_works":["https://openalex.org/W2357124094","https://openalex.org/W2387399993","https://openalex.org/W2389739210","https://openalex.org/W2348924972","https://openalex.org/W2365736347","https://openalex.org/W2047454415","https://openalex.org/W2070040999","https://openalex.org/W2387293848","https://openalex.org/W3121791438","https://openalex.org/W2250140200"],"abstract_inverted_index":{"Online":[0],"business":[1,16],"has":[2],"grown":[3],"exponentially":[4],"during":[5],"the":[6,10,44,57,66,77,98,101,110,113,120,127,137,142,145,160,164],"last":[7],"decade,":[8],"and":[9,27,36,47,76,94,129,172],"industries":[11,75],"are":[12,40,156],"focusing":[13],"on":[14,96],"online":[15,25,61,70,92,107],"more":[17,170],"than":[18],"before.":[19],"However,":[20],"just":[21],"setting":[22],"up":[23],"an":[24],"store":[26],"starting":[28],"selling":[29],"might":[30],"not":[31],"work.":[32],"Different":[33],"machine":[34],"learning":[35,81,139],"data":[37],"mining":[38],"techniques":[39],"needed":[41],"to":[42,56],"know":[43,48],"users\u2019":[45],"preferences":[46],"what":[49],"would":[50],"be":[51],"best":[52],"for":[53,91],"business.":[54],"According":[55],"decision-making":[58],"needs":[59],"of":[60,69,79,100,106,123,132,148,154],"product":[62,71],"sales,":[63],"combined":[64],"with":[65,119],"influencing":[67],"factors":[68],"sales":[72,87,175],"in":[73,103,174],"various":[74],"advantages":[78,147],"deep":[80],"algorithm,":[82],"this":[83],"paper":[84],"constructs":[85],"a":[86],"prediction":[88],"model":[89,102,116,140,150,168],"suitable":[90],"products":[93,155],"focuses":[95],"evaluating":[97],"adaptability":[99],"different":[104,152],"types":[105],"products.":[108],"In":[109,158],"research":[111],"process,":[112],"full":[114],"connection":[115],"is":[117,169],"compared":[118],"training":[121],"results":[122],"CNN,":[124],"which":[125],"proves":[126],"accuracy":[128],"generalization":[130],"ability":[131],"CNN":[133,149,167],"model.":[134],"By":[135],"selecting":[136],"non-deep":[138],"as":[141],"comparison":[143],"baseline,":[144],"performance":[146],"under":[151],"categories":[153],"proved.":[157],"addition,":[159],"experiment":[161],"concludes":[162],"that":[163],"unsupervised":[165],"pretrained":[166],"effective":[171],"adaptable":[173],"forecasting.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}