Algorithmic Primitives For Aligning and Merging Complex Networks

Abstract

In the course of working on Phase II of the DARPA Modeling Adversarial Activity (MAA) program, we have worked to further develop our Multiplex Graph Matching Matched filter methodology, focusing on extending our core approach to the very large, richly featured networks that were the focus of MAA Phase II. We further worked to refine and extend our open source R code-base, denoted iGraphMatch which is available for download on CRAN for robust simulation of correlated graph pairs, efficient implementation of a suite of matching approaches, and novel matching visualization methods. We produced illustrative simulations and data analyses on MAA provided data and on externally provided real data sources.

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Document Details

Document Type
Technical Report
Publication Date
Dec 11, 2023
Accession Number
AD1216394

Entities

People

  • Ben Johnson
  • Carey E. Priebe
  • Daniel L. Sussman
  • Vince Lyzinski
  • Youngser Park

Organizations

  • University of Maryland

Tags

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Big Data
  • Change Detection
  • Data Analysis
  • Data Science
  • Data Sets
  • Detection
  • Engineering
  • Filters
  • Governments
  • Information Science
  • Matched Filters
  • Network Science
  • Simulations
  • Statistics

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Radio communications and signal processing.
  • Systems Analysis and Design