Sathappan Muthiah, Patrick Butler, Rupinder Paul Khandpur, Parang Saraf, Nathan Self, Liang Zhao, Jose Cadena, Chang-Tien Lu, Anil Vullikanti, Achla Marathe, Kristen Summers, Graham Katz, Andy Doyle, Jaime Arredondo, Dipak Gupta, David Mares, Naren Ramakrishnan

Abstract

EMBERS is an anticipatory intelligence system forecasting population-level events in multiple countries of Latin America. A deployed system from 2012, EMBERS has been generating alerts 24x7 by ingesting a broad range of data sources including news, blogs, tweets, machine coded events,currency rates, and food prices. In this paper, we describe our experiences operating EMBERS continuously for nearly 4 years, with specific attention to the discoveries it has enabled, correct as well as missed forecasts, lessons learnt from participating in a forecasting tournament, and our perspectives on the limits of forecasting including ethical considerations.

People

Sathappan Muthiah


Liang Zhao


Naren Ramakrishnan


Nathan Self


Parang Saraf


Patrick Butler


Chang-Tien Lu


Publication Details

Date of publication:
August 15, 2016
Conference:
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining