Node Alertness Detecting Changes In Rapidly Evolving Large Graphs: A Preprint

01 Jul 2019

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 ļ¬nancial local alertness application for cointegrated stock pairs.

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

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Published online at Cornell University