Home › Entities › academia › Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly

Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly

Research article (Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining, 2022) · cited 12× · AI/ML
academia openalex:W4213023867
Press Enter · cited answer in seconds

Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly

Summary

Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly is a scholarly article[1].

Key Facts

  • Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly's instance of is recorded as scholarly article[2].

Related Entities

Kira Radinsky

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly. Retrieved May 24, 2026, from https://4ort.xyz/entity/leveraging-world-events-to-predict-e-commerce-consumer-demand-under-anomaly
MLA “Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/leveraging-world-events-to-predict-e-commerce-consumer-demand-under-anomaly.
BibTeX @misc{4ortxyz_leveraging-world-events-to-predict-e-commerce-consumer-demand-under-anomaly_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly}}, year = {2026}, url = {https://4ort.xyz/entity/leveraging-world-events-to-predict-e-commerce-consumer-demand-under-anomaly}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly — https://4ort.xyz/entity/leveraging-world-events-to-predict-e-commerce-consumer-demand-under-anomaly (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/leveraging-world-events-to-predict-e-commerce-consumer-demand-under-anomaly · Last refreshed: