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 Concept Videos

Impact of Social Context on Individuals01:21

Impact of Social Context on Individuals

Social psychology examines how the real or imagined presence of others influences individuals' thoughts, feelings, and behaviors. A key concept in this field is the role of social context in shaping behavior. The same individual may act differently depending on the social setting, due to the varying expectations and norms associated with each environment. This context-dependent behavior illustrates the influence of social roles, which prescribe appropriate conduct in specific situations.Social...
Relationship Formation02:12

Relationship Formation

What do you think is the single most influential factor in determining with whom you become friends and whom you form romantic relationships? You might be surprised to learn that the answer is simple: the people with whom you have the most contact. This most important factor is proximity. You are more likely to be friends with people you have regular contact with. For example, there are decades of research that shows that you are more likely to become friends with people who live in your dorm,...
Structuralism01:26

Structuralism

Structuralism, an early psychological theory developed by Wilhelm Wundt and his student Edward Bradford Titchener, sought to dissect the human mind into its most fundamental components. Wundt's groundbreaking work in his laboratory set the stage for Titchener to define structuralism's goal as cataloging the "atoms" of the mind—sensations, images, and feelings—akin to how chemists identify elements of matter.
Titchener's approach to structuralism was unique. He employed introspection, a method...
Causes of Similarity-Dissimilarity Effect01:26

Causes of Similarity-Dissimilarity Effect

The similarity-dissimilarity effect, a fundamental concept in social psychology, explains how interpersonal similarities and differences influence attraction and social interactions. This effect is supported by three key psychological perspectives: balance theory, social comparison theory, and consensual validation.Balance Theory and Cognitive ConsistencyBalance theory, developed by Fritz Heider, posits that individuals seek cognitive consistency in their relationships. When two people share...
Social Loafing01:37

Social Loafing

Another way in which a group presence can affect performance is social loafing—the exertion of less effort by a person working together with a group. Social loafing occurs when our individual performance cannot be evaluated separately from the group. Thus, group performance declines on easy tasks (Karau & Williams, 1993). Essentially individual group members loaf and let other group members pick up the slack. Because each individual’s efforts cannot be evaluated, individuals become less...
Social Foundations of Self II: The Generalized Other01:20

Social Foundations of Self II: The Generalized Other

According to George Herbert Mead, as children progress beyond the game stage, they develop a more comprehensive understanding of societal rules and norms. This cognitive and social development enables them to internalize the expectations of the broader community, refining their ability to regulate behavior.Consistent participation in organized activities is crucial in helping children recognize that their actions are not isolated but contribute to a more significant, interconnected group effort.

You might also read

Related Articles

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

Sort by
Same author

A comparison of peripheral imaging technologies for bone and muscle quantification: a technical review of image acquisition.

Journal of musculoskeletal & neuronal interactions·2016
Same author

A de novo mutation in KIT causes white spotting in a subpopulation of German Shepherd dogs.

Animal genetics·2012
Same author

PFS Clustering Method.

IEEE transactions on pattern analysis and machine intelligence·2011
Same author

DECA: A Discrete-Valued Data Clustering Algorithm.

IEEE transactions on pattern analysis and machine intelligence·2011
Same author

Entropy and distance of random graphs with application to structural pattern recognition.

IEEE transactions on pattern analysis and machine intelligence·2011
Same author

Structuring free space as a hypergraph for roving robot path planning and navigation.

IEEE transactions on pattern analysis and machine intelligence·2011
Same journal

HardFlow: Hard-Constrained Sampling for Flow-Matching Models Via Trajectory Optimization.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Industrial Brain: Self-Evolving Neuro-Symbolic Autonomy with Causal Resilience for Cyber-Physical Systems.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Adaptive Hardness-Driven Dictionary Distillation for Incomplete Streaming View Clustering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Mixture of Global and Local Experts with Diffusion Transformer for Controllable Face Generation.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Task-KV: Task-aware KV Cache Optimization via Semantic Differentiation of Attention Heads.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Achieving Text-based Person Retrieval with Any Granularity.

IEEE transactions on pattern analysis and machine intelligence·2026
See all related articles

Related Experiment Video

Updated: May 29, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Random graphs: structural-contextual dichotomy.

A K Wong1, D E Ghahraman

  • 1MEMBER, IEEE, Department of Systems Design, University of Waterloo, Waterloo, Ont., Canada.

IEEE Transactions on Pattern Analysis and Machine Intelligence
|August 27, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a formal definition for random graphs, crucial for graphical pattern recognition. It rigorously defines structural and contextual variability, enabling precise measurement of graph typicality.

More Related Videos

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Related Experiment Videos

Last Updated: May 29, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Area of Science:

  • Graph theory
  • Pattern recognition
  • Statistical modeling

Background:

  • Graphical pattern recognition relies on understanding graph structures.
  • Existing models may not fully capture both structural and contextual variations in graphs.
  • A rigorous framework is needed to analyze random graphs in pattern recognition.

Purpose of the Study:

  • To introduce a formal definition of random graphs applicable to graphical pattern recognition.
  • To rigorously formulate the structural-contextual dichotomy of random graphs.
  • To develop methods for quantifying the typicality of outcome graphs within a random graph framework.

Main Methods:

  • Formal definition of random graphs.
  • Formulation of structural-contextual dichotomy.
  • Probability modeling of outcome graphs.
  • Estimation of probability, typicality, and entropy measures.
  • Interpretation of signed digraph ensembles as outcome graphs.
  • Quantification of typicality using a synthesized random graph.

Main Results:

  • A formal definition of random graphs is presented for pattern recognition.
  • The probability of outcome graphs is decomposed into structural and contextual variability terms.
  • Expressions for estimating probability, typicality, and entropy are derived.
  • A synthesized random graph is used to quantify typicality measures.

Conclusions:

  • The proposed definition and methods provide a rigorous framework for analyzing random graphs in pattern recognition.
  • The structural-contextual dichotomy is formally established.
  • The approach allows for quantitative assessment of graph typicality, aiding in pattern recognition tasks.