Co-Author: Mirco A. Mannucci HoloMathics, LLC mirco@holomathics.com

Co-Author: Deborah Tylor Tylor Data Services, LLC dtylor@tylordata.com

Abstract In this article we describe a new approach for detecting changes in rapidly evolving large-scale graphs. The key notion involved is local alertness: nodes monitor change within their neighborhoods at each time step. Here we propose a financial local alertness application for cointegrated stock pairs.

Keywords spark * pregel * real-time data processing * big data * financial monitoring * graph processing

Read Node Alertness Detecting Changes In Rapidly Evolving Large Graphs

Published online at Cornell University