Premium
Information processing in similarity judgments
Author(s) -
Barthélemy J.P.,
Mullet E.
Publication year - 1996
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1111/j.2044-8317.1996.tb01086.x
Subject(s) - decidability , similarity (geometry) , flowchart , mathematics , basis (linear algebra) , process (computing) , bounded function , reliability (semiconductor) , data mining , algorithm , computer science , theoretical computer science , artificial intelligence , mathematical analysis , power (physics) , physics , geometry , quantum mechanics , image (mathematics) , programming language , operating system
To account for expert information processing of similarity judgments on objects characterized by several attributes, a flexible model, inspired by works of Montgomery (1983) and Barthélemy & Mullet (1986, 1992) is presented and illustrated on the basis of data collected from experienced subjects. This model coordinates three types of rules: threshold rules, conjunctive rules and disjunctive rules. It is based on the principle that a ‘bounded consensus rule’ is the major rule and that all others are merely employed to obtain a consensus structure quickly. Three basic principles are incorporated in the model: (i) a parsimony principle, (ii) a reliability principle, (iii) a decidability principle. The model can be represented as a process (flowchart) or as a formula (equation).
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom