Detecting intra- and inter-categorical structure in semantic concepts using HICLAS.

In this paper, we investigate the hypothesis that people use feature correlations to detect inter- and intra-categorical structure. More specifically, we study whether it is plausible that people strategically look for a particular type of feature co-occurrence that can be represented in terms of rectangular patterns of 1s and 0s in a binary feature by exemplar matrix. Analyzing data from the Animal and Artifact domains, we show that the HICLAS model, which looks for such rectangular structure and which therefore models a cognitive capacity of detecting feature co-occurence in large data bases of features characterizing exemplars, succeeds rather well in predicting inter- and intra-categorical structure.

[1]  Gerrit Storms,et al.  Exemplar Models in the Study of Natural Language Concepts , 2004 .

[2]  Gert Storms,et al.  Categorization of novel stimuli in well-known natural concepts: A case study , 2001, Psychonomic bulletin & review.

[3]  Steven A. Sloman,et al.  Artifacts are not ascribed essences, nor are they treated as belonging to kinds , 2003 .

[4]  Gert Storms,et al.  Linear separability in superordinate natural language concepts , 2004, Memory & cognition.

[5]  James L. McClelland,et al.  Semantic Cognition: A Parallel Distributed Processing Approach , 2004 .

[6]  E. Rosch,et al.  Family resemblances: Studies in the internal structure of categories , 1975, Cognitive Psychology.

[7]  Iven Van Mechelen,et al.  Bayesian Hierarchical Classes Analysis , 2008 .

[8]  J. Hampton.  Polymorphous Concepts in Semantic Memory , 1979 .

[9]  G. Murphy,et al.  The Big Book of Concepts , 2002 .

[10]  G. Kellas,et al.  Typicality as a Dimension of Encoding. , 1978 .

[11]  Vikash K. Mansinghka,et al.  Learning Cross-cutting Systems of Categories , 2006 .

[12]  U. Neisser.  Concepts and Conceptual Development: Ecological and Intellectual Factors in Categorization , 1989 .

[13]  M. McCloskey,et al.  Natural categories: Well defined or fuzzy sets? , 1978 .

[14]  Edward E. Smith,et al.  Categories and concepts , 1984 .

[15]  Thomas L. Griffiths,et al.  Learning Systems of Concepts with an Infinite Relational Model , 2006, AAAI.

[16]  Lawrence W. Barsalou,et al.  The instability of graded structure: implications for the nature of concepts , 1987 .

[17]  Iven Van Mechelen,et al.  Hierarchical classes models for three-way three-mode binary data: interrelations and model selection , 2005 .

[18]  J. D. Smith,et al.  Thirty categorization results in search of a model. , 2000, Journal of experimental psychology. Learning, memory, and cognition.

[19]  I. Mechelen,et al.  Structural analysis of the intension and extension of semantic concepts , 1994 .

[20]  Ryszard S. Michalski,et al.  Categories and Concepts: Theoretical Views and Inductive Data Analysis , 1993 .

[21]  Michael D Lee,et al.  Finding the features that represent stimuli. , 2010, Acta psychologica.

[22]  P. Boeck,et al.  Hierarchical classes: Model and data analysis , 1988 .

[23]  Hans-Hermann Bock,et al.  Two-mode clustering methods: astructuredoverview , 2004, Statistical methods in medical research.

[24]  Steven A. Sloman,et al.  How bilinguals solve the naming problem , 2005 .

[25]  Tim Smits,et al.  Fruits and vegetables categorized: An application of the generalized context model , 2002, Psychonomic bulletin & review.

[26]  Jack Sutcliffe,et al.  Concept, Class, And Category In The Tradition Of Aristotle , 1993 .

[27]  Wolf Vanpaemel,et al.  Exemplar by feature applicability matrices and other Dutch normative data for semantic concepts , 2008, Behavior research methods.

[28]  Gerrit Storms.  Flemish Category Norms for Exemplars of 39 Categories: A Replication of the Battig and Montague (1969) Category Norms , 2001 .

[29]  H. Kiers,et al.  Selecting among three-mode principal component models of different types and complexities: a numerical convex hull based method. , 2006, The British journal of mathematical and statistical psychology.

[30]  Wolf Vanpaemel,et al.  Dutch norm data for 13 semantic categories and 338 exemplars , 2004, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[31]  Iven Van Mechelen,et al.  The Local Minima Problem in Hierarchical Classes Analysis: An Evaluation of a Simulated Annealing Algorithm and Various Multistart Procedures , 2007 .

[32]  D. Medin,et al.  Are there kinds of concepts? , 2000, Annual review of psychology.

[33]  David L. Faigman,et al.  Human category learning. , 2005, Annual review of psychology.

[34]  J. Hampton.  Concepts as Prototypes , 2006 .

[35]  Gerrit Storms,et al.  Prototype and Exemplar-Based Information in Natural Language Categories , 2000 .

[36]  Wayne D. Gray,et al.  Basic objects in natural categories , 1976, Cognitive Psychology.

[37]  J. Mandler.  Perceptual and Conceptual Processes in Infancy , 2000 .

[38]  Jeffrey J. Starns,et al.  False memories lack perceptual detail: Evidence from implicit word-stem completion and perceptual identification tests , 2005 .

[39]  Iven Van Mechelen,et al.  An Evaluation of Two Algorithms for Hierarchical Classes Analysis , 2001, J. Classif..

[40]  Edward E. Smith,et al.  Category-Based Induction , 1990 .

[41]  G. Bower,et al.  THE PSYCHOLOGY OF LEARNING AND M·OTIVATION , 2001 .

[42]  A. Tversky.  Features of Similarity , 1977 .

[43]  R. Nosofsky.  Attention, similarity, and the identification-categorization relationship. , 1986, Journal of experimental psychology. General.