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

Sorting out categories: incremental learning of category structure.

Michael Diaz1, Brian H Ross

  • 1Department of Psychology, University of Illinois, 603 East Daniel Street, Champaign, IL 61820, USA. mikediaz@uiuc.edu

Psychonomic Bulletin & Review
|August 9, 2006
PubMed
Summary
This summary is machine-generated.

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

Novel driver gene MDC1 confers homologous recombination repair deficiency and genomic instability in chemoresistant relapsing ovarian cancer.

Journal of translational medicine·2026
Same author

An integrated workflow for structural virology with a 100 keV electron microscope.

bioRxiv : the preprint server for biology·2025
Same author

Exome sequencing identifies HELB as a novel susceptibility gene for non-mucinous, non-high-grade-serous epithelial ovarian cancer.

European journal of human genetics : EJHG·2025
Same author

Exome sequencing identifies <i>HELB</i> as a novel susceptibility gene for non-mucinous, non-high-grade-serous epithelial ovarian cancer.

medRxiv : the preprint server for health sciences·2024
Same author

Neonatal mortality risk of vulnerable newborns by fine stratum of gestational age and birthweight for 230 679 live births in nine low- and middle-income countries, 2000-2017.

BJOG : an international journal of obstetrics and gynaecology·2024
Same author

Neonatal mortality risk of vulnerable newborns: A descriptive analysis of subnational, population-based birth cohorts for 238 203 live births in low- and middle-income settings from 2000 to 2017.

BJOG : an international journal of obstetrics and gynaecology·2023
Same journal

Mind wandering during first- and foreign-language reading.

Psychonomic bulletin & review·2026
Same journal

Lexical word processing is unaffected by rapid invisible frequency tagging in reading: Evidence from eye movements.

Psychonomic bulletin & review·2026
Same journal

Anxiety modulates voluntary attentional orienting to emotional gaze cues: Eye movements for pro- and anti-saccades.

Psychonomic bulletin & review·2026
Same journal

Faster key-press responses to front vowels than back vowels when matching heard vowels with represented vowels.

Psychonomic bulletin & review·2026
Same journal

Testing the interleaving effect without response bias: A forced-choice reevaluation of Kornell and Bjork (2008).

Psychonomic bulletin & review·2026
Same journal

The impact of social interaction on abstract concepts.

Psychonomic bulletin & review·2026
See all related articles

Pairwise inferences aid incremental category learning by influencing feature weightings and sorting, building a foundation for understanding complex family resemblance structures.

Area of Science:

  • Cognitive Psychology
  • Machine Learning
  • Artificial Intelligence

Background:

  • Categories are often defined by overall similarity (family resemblance) rather than single features.
  • People tend to sort items based on single features, even when family resemblance is key.
  • Previous research shows pairwise inferences can increase family resemblance sorting.

Purpose of the Study:

  • To investigate how pairwise inferences promote unsupervised and incremental category learning.
  • To understand the mechanism by which inferences lead to learning family resemblance structures.

Main Methods:

  • Two experiments were conducted using a category construction task.
  • Participants made pairwise inferences about category members.
  • Feature weightings and sorting behavior were analyzed to track learning.

Related Experiment Videos

Main Results:

  • Category structure is learned incrementally through a process influenced by inferences.
  • Pairwise inferences specifically affected the weighting of queried feature pairs.
  • This altered weighting influenced participants' sorting, which in turn facilitated further learning.

Conclusions:

  • Inferences do not directly reveal family resemblance structures but provide a crucial foundation.
  • The learning process is incremental, with sorting acting as a bridge to further understanding.
  • This sheds light on how humans learn complex categories without explicit feature definitions.