Abstract: Techniques for predicting an impact of one or more events on service demand are disclosed. Some embodiments include first and second sets of data characterising properties of historic events using metadata tags, and demand for services that are then filtered to distinguish ordinary demand from extra-ordinary demand. Machine learning is used to determine correlations between metadata tags and extra-ordinary demand to produce a third data set operable for predictive determinations of future event on service demand.
Type:
Application
Filed:
March 30, 2020
Publication date:
June 9, 2022
Applicant:
Predict HQ Limited
Inventors:
Campbell Brown, Xuxu Wang, Robert Kern, Ali GAZALA