Effects of background knowledge on object categorization and part detection.

Abstract

Previous research has shown that background knowledge affects the ease of concept learning, but little research has examined its effects on speeded categorization of instances after the category is well learned. Subjects in 4 experiments first learned novel categories. At test, they categorized a new set of novel stimuli that were either consistent or inconsistent with background knowledge given about the categories. Background knowledge affected categorization responses in an untimed task, with usual reaction time instructions, with a response deadline, or when the stimuli were presented for 50 ms followed by a mask. Three other experiments using a part-detection task showed that subjects were more likely to notice missing parts that were critical than noncritical according to background knowledge. The mechanisms by which background knowledge affects categorization and part detection are discussed. Human categorization is a cognitive proceSs in which people decide whether an instance is a member of a category by comparing the instance with their conceptual representations. Categorization research in the 1970s and early 1980s primarily focused on certain issues of representation, such as whether concepts are represented by prototypes (summary representations of an entire category) or by exemplars (individual instances of the categories). Despite the differences between these models of conceptual representation, they share some common assumptions. One assumption is that concepts are collections of features; another is that categorization involves feature matching and computation of feature similarity between the instance to be categorized and the concept with which the instance is compared (see Smith & Medin, 1981, for a review). More recently, however, a growing number of researchers