{"id":"https://openalex.org/W2995885162","doi":"https://doi.org/10.1145/3371238.3371256","title":"Statistical and Machine Learning-based E-commerce Sales Forecasting","display_name":"Statistical and Machine Learning-based E-commerce Sales Forecasting","publication_year":2019,"publication_date":"2019-10-18","ids":{"openalex":"https://openalex.org/W2995885162","doi":"https://doi.org/10.1145/3371238.3371256","mag":"2995885162"},"language":"en","primary_location":{"id":"doi:10.1145/3371238.3371256","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3371238.3371256","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th International Conference on Crowd Science and Engineering","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/A5043669751","display_name":"Wenxiang Dong","orcid":"https://orcid.org/0000-0002-0272-1069"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxiang Dong","raw_affiliation_strings":["Dept. of Automation and Inst. for Artificial Intelligence, Tsinghua, Univ. Beijing National Research Center for Info. Science and Technology (BNRist), Beijing, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Automation and Inst. for Artificial Intelligence, Tsinghua, Univ. Beijing National Research Center for Info. Science and Technology (BNRist), Beijing, P.R.China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101607289","display_name":"Qingming Li","orcid":"https://orcid.org/0000-0001-7410-4345"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingming Li","raw_affiliation_strings":["Dept. of Automation and Inst. for Artificial Intelligence, Tsinghua Univ., Beijing National Research Center for Info. Science and Technology (BNRist), Beijing, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Automation and Inst. for Artificial Intelligence, Tsinghua Univ., Beijing National Research Center for Info. Science and Technology (BNRist), Beijing, P.R.China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017692278","display_name":"Hongke Zhao","orcid":"https://orcid.org/0000-0003-3099-4803"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"H. Vicky Zhao","raw_affiliation_strings":["Dept. of Automation and Inst. for Artificial Intelligence, Tsinghua Univ., Beijing National Research Center for Info. Science and Technology (BNRist), Beijing, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Automation and Inst. for Artificial Intelligence, Tsinghua Univ., Beijing National Research Center for Info. Science and Technology (BNRist), Beijing, P.R.China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.6656,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.69968631,"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":"110","last_page":"117"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9776999950408936,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"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/T12659","display_name":"Innovation Diffusion and Forecasting","score":0.9563999772071838,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.8059079647064209},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6673949956893921},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6460038423538208},{"id":"https://openalex.org/keywords/sales-forecasting","display_name":"Sales forecasting","score":0.5239063501358032},{"id":"https://openalex.org/keywords/sales-management","display_name":"Sales management","score":0.45933547616004944},{"id":"https://openalex.org/keywords/incentive","display_name":"Incentive","score":0.4238497018814087},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4175061881542206},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3967093527317047},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3230006694793701},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.3121539354324341},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3012363910675049},{"id":"https://openalex.org/keywords/marketing","display_name":"Marketing","score":0.2365243136882782},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.1747332513332367},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.11845606565475464}],"concepts":[{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.8059079647064209},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6673949956893921},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6460038423538208},{"id":"https://openalex.org/C2984642479","wikidata":"https://www.wikidata.org/wiki/Q7404320","display_name":"Sales forecasting","level":2,"score":0.5239063501358032},{"id":"https://openalex.org/C139749660","wikidata":"https://www.wikidata.org/wiki/Q5657855","display_name":"Sales management","level":2,"score":0.45933547616004944},{"id":"https://openalex.org/C29122968","wikidata":"https://www.wikidata.org/wiki/Q1414816","display_name":"Incentive","level":2,"score":0.4238497018814087},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4175061881542206},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3967093527317047},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3230006694793701},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.3121539354324341},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3012363910675049},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.2365243136882782},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.1747332513332367},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.11845606565475464},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3371238.3371256","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3371238.3371256","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th International Conference on Crowd Science and Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1979383090","https://openalex.org/W1992339772","https://openalex.org/W2012501109","https://openalex.org/W2051616972","https://openalex.org/W2061843519","https://openalex.org/W2067505258","https://openalex.org/W2090786120","https://openalex.org/W2585078266","https://openalex.org/W2744043447","https://openalex.org/W2775634393","https://openalex.org/W2807541381"],"related_works":["https://openalex.org/W3175321409","https://openalex.org/W4328094257","https://openalex.org/W4312561791","https://openalex.org/W2389894046","https://openalex.org/W2215717369","https://openalex.org/W4312309719","https://openalex.org/W4313123484","https://openalex.org/W2674988168","https://openalex.org/W2146461990","https://openalex.org/W4200142652"],"abstract_inverted_index":{"Market":[0],"share":[1],"analysis":[2],"and":[3,24,29,94,110,119,131],"sales":[4,20],"forecasting":[5],"have":[6],"always":[7],"been":[8],"an":[9],"important":[10,133],"research":[11,40],"area.":[12],"It":[13],"is":[14],"of":[15,37,76,81,121,125],"great":[16],"significance":[17],"to":[18,27,31,64,68,73,135],"predict":[19,69],"through":[21],"existing":[22],"information":[23],"provide":[25,132],"guidance":[26],"merchants":[28,136],"markets":[30],"obtain":[32],"higher":[33],"profits.":[34],"However,":[35],"most":[36],"the":[38,57,61,66,70,74,104,117,122],"traditional":[39],"focuses":[41],"on":[42,127,137],"brick-and-mortar":[43],"retail":[44],"stores,":[45],"while":[46],"few":[47],"works":[48],"studied":[49],"E-commerce":[50],"markets.":[51],"In":[52],"this":[53],"paper,":[54],"we":[55],"use":[56],"historical":[58],"data":[59,112,129],"in":[60],"e-commerce":[62],"market":[63],"establish":[65],"model":[67],"sales.":[71],"According":[72],"characteristics":[75],"different":[77,107,111,128],"data,":[78],"three":[79,99,123],"types":[80,124],"prediction":[82],"models":[83,126],"are:":[84],"Incentive":[85],"Auto":[86],"Regressive":[87],"Integrated":[88],"Moving":[89],"Average(I-ARIMA),":[90],"Long":[91],"Short-Term":[92],"Memory(LSTM)":[93],"Artificial":[95],"Neural":[96],"Network(ANN).":[97],"These":[98],"methods":[100],"can":[101],"deal":[102],"with":[103,106],"problem":[105],"accuracy":[108],"requirements":[109],"types.":[113],"This":[114],"paper":[115],"studies":[116],"advantages":[118],"disadvantages":[120],"sets,":[130],"guidelines":[134],"their":[138],"marketing":[139],"strategies.":[140]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}