Joint European Conference on Machine Learning and Knowledge Discovery in Databases

ECML PKDD 2015: Machine Learning and Knowledge Discovery in Databases pp 320-324 | Cite as

S&P360: Multidimensional Perspective on Companies from Online Data Sources

  • Michele Berlingerio
  • Stefano Braghin
  • Francesco Calabrese
  • Cody Dunne
  • Yiannis Gkoufas
  • Mauro Martino
  • Jamie Rasmussen
  • Steven Ross
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9286)

Abstract

We introduce S&P360, a system to analyse and explore multidimensional, online data related to companies, their financial news, and the social impact of them. Our system combines official and crowd-sourced data sources to offer a broad perspective on the impact of financial newsregarding a set of companies.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Berlingerio, M., Pinelli, F., Calabrese, F.: ABACUS: frequent pattern mining-based community discovery in multidimensional networks. Data Min. Know. Dis. 27(3), 294–320 (2013)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Michele Berlingerio
    • 1
  • Stefano Braghin
    • 1
  • Francesco Calabrese
    • 1
  • Cody Dunne
    • 2
  • Yiannis Gkoufas
    • 1
  • Mauro Martino
    • 2
  • Jamie Rasmussen
    • 2
  • Steven Ross
    • 2
  1. 1.IBM Research IrelandDublinIreland
  2. 2.IBM WatsonYorktown HeightsUSA

Personalised recommendations