Object categorization: Reversals and explanations of the basic-level advantage.

Abstract

People are generally faster and more accurate to name or categorize objects at the basic level (e.g., dog) relative to more general (animal) or specific (collie) levels, an effect replicated in Experiment 1 for categorization of object pictures. To some, this pattern suggests a dual-process mechanism, in which objects first activate basic-level categories directly and later engage more general or specific categories through the spread of activation in a processing hierarchy. This account is, however, challenged by data from Experiment 2 showing that neuropsychological patients with impairments of conceptual knowledge categorize more accurately at superordinate levels than at the basic level-suggesting that knowledge about an object's general nature does not depend on prior basic-level categorization. The authors consider how a parallel distributed processing theory of conceptual knowledge can reconcile the apparent discrepancy. This theory predicts that if healthy individuals are encouraged to make rapid categorization responses, the usual basic Ͼ general advantage should also reverse, a prediction tested and confirmed in Experiment 3. Implications for theories of visual object recognition are discussed.

“Object Categorization: Reversals and Explanations of the Basic-Level Advantage” (Rogers & Patterson, 2007): A simplicity account

“…As a consequence of this, the overall codelength for classification at this level is high, reflecting the fact that using superordinate categories provides only a minor simplification in the description of the 'raw' similarity information. Classification at the subordinate level is also prejudiced: while in this case most constraints are of category specificity and informativeness (e.g., Komatsu, 1992;Medin, 1986;Murphy & Brownell, 1985;Murphy & Smith, 1982).How do the predictions of the simplicity model map onto the standard empirical finding that people are generally faster and more accurate to categorise a presented stimulus at the basic level (e.g., bird) than at either the superordinate (e.g., animal) or subordinate (e.g., Robin) levels (Rogers & Patterson, 2007;Rosch et al, 1976)? The assumption is that, given their high level of intuitiveness, the category structures that represent classification at the basic level will simply be more readily accessible than the category structures that represent classification at the superordinate and subordinate levels (which are not very intuitive): that is, superordinate and subordinate level categorisations will be cognitively more effortful and time-consuming to perceive.…”

User-centric query refinement and processing using granularity-based strategies

“…Thus, a hierarchical granular structure is formed based on these levels of results. Psychological experiments have proofed that human prefers to solve problems using terms in the basic level (the ones that are used more frequently than others [35]), and in this way the problem-solving process can be accelerated [30]. In the upper example, "Tom Mitchell" can be considered as a term in the basic level for machine learning researchers.…”

“…Besides the inspiration from granular computing [39,43], the strategies are also inspired from Cognitive Psychology (e.g. basic level) [30,34]. Further, we concentrate on how granularity-based strategies can help to effectively solve large-scale reasoning problems according to different user context and time constraints.…”

“…All the levels form a hierarchical granular structure. According to the basic-level advantage in cognitive science [30,34], we propose a "starting point" that consists of an input query together with additional constraints derived from a user profile (such as users interests, etc. They help the search process locate to an appropriate level that is convenient to accelerate the process of finding useful results).…”

A Naturalistic Approach to the Generality Problem

“…Rogers and Patterson (2007), p. 451: "… basic level effects are among the best known and most robust phenomena in the study of human categorization." Thus, given that something is a chair, it can be inferred that the thing has legs, a seat, and so on.…”