{"id":"https://openalex.org/W4213023867","doi":"https://doi.org/10.1145/3488560.3498452","title":"Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly","display_name":"Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly","publication_year":2022,"publication_date":"2022-02-11","ids":{"openalex":"https://openalex.org/W4213023867","doi":"https://doi.org/10.1145/3488560.3498452"},"language":"en","primary_location":{"id":"doi:10.1145/3488560.3498452","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488560.3498452","pdf_url":null,"source":{"id":"https://openalex.org/S4363608885","display_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","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":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2405.13995","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022063260","display_name":"Dan Kalifa","orcid":"https://orcid.org/0000-0001-6459-6833"},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Dan Kalifa","raw_affiliation_strings":["Technion, Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"Technion, Haifa, Israel","institution_ids":["https://openalex.org/I174306211"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079470269","display_name":"Uriel Singer","orcid":"https://orcid.org/0000-0001-8451-8533"},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Uriel Singer","raw_affiliation_strings":["Technion, Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"Technion, Haifa, Israel","institution_ids":["https://openalex.org/I174306211"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035284207","display_name":"Ido Guy","orcid":"https://orcid.org/0000-0002-5525-1064"},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Ido Guy","raw_affiliation_strings":["Ben-Gurion University of the Negev, Beer Sheva, Israel"],"affiliations":[{"raw_affiliation_string":"Ben-Gurion University of the Negev, Beer Sheva, Israel","institution_ids":["https://openalex.org/I124227911"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110931115","display_name":"Guy Rosin","orcid":null},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Guy D. Rosin","raw_affiliation_strings":["Technion, Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"Technion, Haifa, Israel","institution_ids":["https://openalex.org/I174306211"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029708595","display_name":"Kira Radinsky","orcid":"https://orcid.org/0009-0007-7918-2204"},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Kira Radinsky","raw_affiliation_strings":["Technion, Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"Technion, Haifa, Israel","institution_ids":["https://openalex.org/I174306211"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5022063260"],"corresponding_institution_ids":["https://openalex.org/I174306211"],"apc_list":null,"apc_paid":null,"fwci":2.3311,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.89153439,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"430","last_page":"438"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.996999979019165,"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":0.996999979019165,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9969000220298767,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9959999918937683,"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":0.7267286777496338},{"id":"https://openalex.org/keywords/e-commerce","display_name":"E-commerce","score":0.5860500335693359},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5064471960067749},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.46327683329582214},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.45546919107437134},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3924912214279175},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3636265993118286},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3615652918815613},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29916197061538696},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.16160625219345093},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.09926554560661316}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7267286777496338},{"id":"https://openalex.org/C78597825","wikidata":"https://www.wikidata.org/wiki/Q484847","display_name":"E-commerce","level":2,"score":0.5860500335693359},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5064471960067749},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.46327683329582214},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.45546919107437134},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3924912214279175},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3636265993118286},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3615652918815613},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29916197061538696},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.16160625219345093},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.09926554560661316},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3488560.3498452","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488560.3498452","pdf_url":null,"source":{"id":"https://openalex.org/S4363608885","display_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","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":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2405.13995","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2405.13995","pdf_url":"https://arxiv.org/pdf/2405.13995","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2405.13995","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2405.13995","pdf_url":"https://arxiv.org/pdf/2405.13995","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4213023867.pdf","grobid_xml":"https://content.openalex.org/works/W4213023867.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1689711448","https://openalex.org/W1973167214","https://openalex.org/W1981903823","https://openalex.org/W2030594688","https://openalex.org/W2032927332","https://openalex.org/W2036455044","https://openalex.org/W2048968173","https://openalex.org/W2064675550","https://openalex.org/W2088579613","https://openalex.org/W2585731554","https://openalex.org/W2624385633","https://openalex.org/W2747599906","https://openalex.org/W2751802138","https://openalex.org/W2889059162","https://openalex.org/W2906498146","https://openalex.org/W2945057656","https://openalex.org/W2962731543","https://openalex.org/W2964404039","https://openalex.org/W2988044524","https://openalex.org/W2996361803","https://openalex.org/W2996565520","https://openalex.org/W3000500483","https://openalex.org/W3020096797","https://openalex.org/W3022787740","https://openalex.org/W3080418372","https://openalex.org/W3089610451","https://openalex.org/W3105935311","https://openalex.org/W3116574048","https://openalex.org/W3144036519","https://openalex.org/W3163934814","https://openalex.org/W4239680602","https://openalex.org/W4240429504"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W2037549926","https://openalex.org/W2345479200","https://openalex.org/W2183306018","https://openalex.org/W2849310602","https://openalex.org/W3006008237","https://openalex.org/W2419146053","https://openalex.org/W4388890789","https://openalex.org/W2088247287","https://openalex.org/W2963903416"],"abstract_inverted_index":{"Consumer":[0],"demand":[1],"forecasting":[2,26],"is":[3,29],"of":[4,84,93,96,116,123,153],"high":[5],"importance":[6],"for":[7,27],"many":[8,35,49],"e-commerce":[9,28,145],"applications,":[10],"including":[11],"supply":[12],"chain":[13],"optimization,":[14],"advertisement":[15],"placement,":[16],"and":[17,99],"delivery":[18],"speed":[19],"optimization.":[20],"However,":[21],"reliable":[22],"time":[23,50],"series":[24,51],"sales":[25,147],"difficult,":[30],"especially":[31],"during":[32,41,60,170],"periods":[33],"with":[34],"anomalies,":[36],"as":[37],"can":[38,79],"often":[39],"happen":[40],"pandemics,":[42],"abnormal":[43],"weather,":[44],"or":[45],"sports":[46],"events.":[47,126],"Although":[48],"algorithms":[52],"have":[53],"been":[54],"applied":[55],"to":[56,112,132],"the":[57,82,121,124,140,154],"task,":[58],"prediction":[59,85],"anomalies":[61],"still":[62],"remains":[63],"a":[64,90,106,117,143],"challenge.":[65],"In":[66],"this":[67],"work,":[68],"we":[69,104],"hypothesize":[70],"that":[71,164],"leveraging":[72],"external":[73],"knowledge":[74],"found":[75],"in":[76],"world":[77,97],"events":[78,98],"help":[80],"overcome":[81],"challenge":[83],"under":[86],"anomalies.":[87,171],"We":[88,137,159],"mine":[89],"large":[91,144],"repository":[92],"40":[94],"years":[95],"their":[100],"textual":[101],"representations.":[102],"Further,":[103],"present":[105],"novel":[107],"methodology":[108],"based":[109,119],"on":[110,120],"transformers":[111],"construct":[113],"an":[114],"embedding":[115],"day":[118],"relations":[122],"day's":[125],"Those":[127],"embeddings":[128],"are":[129],"then":[130],"used":[131],"forecast":[133],"future":[134],"consumer":[135],"behavior.":[136],"empirically":[138],"evaluate":[139],"methods":[141],"over":[142,161],"products":[146],"dataset,":[148],"extracted":[149],"from":[150],"eBay,":[151],"one":[152],"world's":[155],"largest":[156],"online":[157],"marketplaces.":[158],"show":[160],"numerous":[162],"categories":[163],"our":[165],"method":[166],"outperforms":[167],"state-of-the-art":[168],"baselines":[169]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2022-02-24T00:00:00"}
