LeveragingWorld events to predict e-commerce consumer demand under anomaly

Dan Kalifa, Uriel Singer, Ido Guy, Guy D. Rosin, Kira Radinsky

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Consumer demand forecasting is of high importance for many e-commerce applications, including supply chain optimization, advertisement placement, and delivery speed optimization. However, reliable time series sales forecasting for e-commerce is difficult, especially during periods with many anomalies, as can often happen during pandemics, abnormal weather, or sports events. Although many time series algorithms have been applied to the task, prediction during anomalies still remains a challenge. In this work, we hypothesize that leveraging external knowledge found in world events can help overcome the challenge of prediction under anomalies. We mine a large repository of 40 years of world events and their textual representations. Further, we present a novel methodology based on transformers to construct an embedding of a day based on the relations of the day's events. Those embeddings are then used to forecast future consumer behavior. We empirically evaluate the methods over a large e-commerce products sales dataset, extracted from eBay, one of the world's largest online marketplaces. We show over numerous categories that our method outperforms state-of-the-art baselines during anomalies.

Original languageEnglish
Title of host publicationWSDM 2022 - Proceedings of the 15th ACM International Conference on Web Search and Data Mining
PublisherAssociation for Computing Machinery, Inc
Pages430-438
Number of pages9
ISBN (Electronic)9781450391320
DOIs
StatePublished - 11 Feb 2022
Event15th ACM International Conference on Web Search and Data Mining, WSDM 2022 - Virtual, Online, United States
Duration: 21 Feb 202225 Feb 2022

Publication series

NameWSDM 2022 - Proceedings of the 15th ACM International Conference on Web Search and Data Mining

Conference

Conference15th ACM International Conference on Web Search and Data Mining, WSDM 2022
Country/TerritoryUnited States
CityVirtual, Online
Period21/02/2225/02/22

Keywords

  • Anomalies
  • E-commerce
  • Forecasting
  • World events

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Software

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