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Guess

  • Living reference work entry
  • First Online:
Encyclopedia of Social Network Analysis and Mining

  • 76 Accesses

Synonyms

Analysis; Domain-specific language; Exploratory data analysis; Graph exploration; Social network analysis; Visualization

Glossary

DSL:

Domain-specific language

Definition

The Graph Exploration System (GUESS) is an open source tool for analysis of networks. Through a combination of a visualization system and a custom language (an extension of Python), GUESS supports many graph types and analyses and can be used in both interactive settings and for deploying applications. It is available at http://graphexploration.cond.org.

Introduction

The Graph Exploration System (GUESS) is a visual analytic tool for processing network structures. While originally targeted at social networks, the system is general in its representation of networks (Adar 2006). Nodes and edges are the key objects which can be extended with any set of properties or relations. Because of this flexibility, the system has been used for everything from modelling food nets to sewer lines and computer network...

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Author information

Authors and Affiliations

  1. School of Information & Computer Science and Engineering, University of Michigan, Ann Arbor, MI, USA

    Eytan Adar

Authors
  1. Eytan Adar
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Corresponding author

Correspondence to Eytan Adar .

Editor information

Editors and Affiliations

  1. Computer Science, University of Calgary, Calgary, Alberta, Canada

    Reda Alhajj

  2. University of Calgary Computer Science, Calgary, Canada

    Jon Rokne

Section Editor information

  1. Department of Mathematics, University of Ljubljana, Ljubljana, Slovenia

    Vladimir Batagelj

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© 2017 Springer Science+Business Media LLC

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Adar, E. (2017). Guess. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7163-9_300-1

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  • DOI: https://doi.org/10.1007/978-1-4614-7163-9_300-1

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-7163-9

  • Online ISBN: 978-1-4614-7163-9

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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