Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Graph theoretic modeling of large-scale semantic networks.

Michael E Bales1, Stephen B Johnson

  • 1Department of Biomedical Informatics, Columbia University, New York, NY, USA. michael.bales@dbmi.columbia.edu

Journal of Biomedical Informatics
|January 31, 2006
PubMed
Summary

Graph theory applied to semantic networks reveals common topological properties found in natural language, similar to other complex systems. This analysis offers potential informatics applications, including controlled vocabularies.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Participatory Ecological Assessment of Farmer Perspectives on Management of Invasive <i>Ageratina adenophora</i> in Eastern Bhutan.

Plant-environment interactions (Hoboken, N.J.)·2026
Same author

Implementing the NYU Electronic Patient Visit Assessment (ePVA)<sup>©</sup> for head and neck cancer in rural and urban populations: a study protocol for a type 1 hybrid effectiveness-implementation clinical trial.

Trials·2025
Same author

Natural Language Processing for Automated Extraction of Continuous Glucose Monitoring Data.

Diabetes care·2025
Same author

Using CTSA infrastructure to address health disparities in New York City communities: Barriers and facilitators to implementing a free health screening program.

Journal of clinical and translational science·2025
Same author

How Difference Tasks Are Affected by Probability Format, Part 2: A Making Numbers Meaningful Systematic Review.

MDM policy & practice·2025
Same author

Classifying Continuous Glucose Monitoring Documents From Electronic Health Records.

Journal of diabetes science and technology·2025

Area of Science:

  • Informatics
  • Computational Biology
  • Network Science

Background:

  • Social network analysis and graph theory are increasingly used to model complex systems.
  • Graph theoretic methods are underutilized in the broader informatics community despite their success in computational biology.
  • Large-scale networks, often derived from semantic information, exhibit complex, sparse, and large topological properties.

Purpose of the Study:

  • To review research (1998-2005) on large-scale semantic networks using a graph theoretic perspective.
  • To identify common topological properties of networks generated from natural language.
  • To explore potential applications of large network analysis in informatics.

Main Methods:

  • Conducted a tailored literature search for articles combining graph theory and semantic information.

Related Experiment Videos

  • Retrieved and analyzed 31 relevant articles published between 1998 and 2005.
  • Focused on studies investigating real-world networks, particularly those comprised of words or phrases.

    • Main Results:

    • The majority of reviewed studies (90.3%) investigated real-world networks, including corpora, thesauri, and biological networks.
    • Graphs comprised of words or phrases were common (78.6%).
    • Evidence of small-world characteristics (53.6%) and scale-free topology (39.3%) was frequently reported.

    Conclusions:

    • Networks derived from natural language share topological properties with other natural phenomena.
    • It remains undetermined if biomedical terminology systems exhibit similar properties.
    • Large network analysis methods show promise for informatics applications like controlled vocabulary development and domain characterization.