Retrieval time from semantic memory

Collins, Allan; Quillian, M. Ross

doi:10.1016/s0022-5371(69)80069-1

Cited by 2,456 publications

(1,430 citation statements)

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“…Jones & Mewhort, 2007). Early theories of semantic networks share a similar logic, where word meaning is acquired via relations with other words (Collins & Quillian, 1969). Nodes are represented by concepts and relationships between them are represented by links, such that words like bird become associated with feathers and animal by links such as Has and Is-a.…”

Section: University Of Warwickmentioning

confidence: 99%

The company that words keep: comparing the statistical structure of child- versus adult-directed language

Hills

2012

J. Child Lang.

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Section: University Of Warwickmentioning

confidence: 99%

The company that words keep: comparing the statistical structure of child- versus adult-directed language

Hills

2012

J. Child Lang.

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“…In hierarchical network theory (Collins & Quillian, 1969), distinctive features are stored at the lowest concept node in the hierarchy to which the feature applies. Thus, 〈moos〉 would be stored at the cow node, whereas 〈eats〉 would be stored at a higher level, such as the animal node.…”

Section: Alternative Predictionsmentioning

confidence: 99%

“…The first models of semantic memory were hierarchical network theory (Collins & Quillian, 1969) and spreading activation theory (Collins & Loftus, 1975). Although both have been extremely influential and have provided predictions for numerous behavioral studies, both have lost favor owing to a number of well-understood and documented flaws (see Rogers & McClelland, 2004, for a recent review).…”

Section: Introductionmentioning

confidence: 99%

“…Although we are far from a complete understanding, significant progress has been made since Tulving (1972) first introduced the term "semantic memory." Much of this progress can be attributed to the implementation and development of semantic memory models and the advancement of tools (e.g., semantic feature production norms and word co-occurrence statistics) that enable the rigorous testing of predictions generated from these models.The first models of semantic memory were hierarchical network theory (Collins & Quillian, 1969) and spreading activation theory (Collins & Loftus, 1975). Although both have been extremely influential and have provided predictions for numerous behavioral studies, both have lost favor owing to a number of well-understood and documented flaws (see Rogers & McClelland, 2004, for a recent review).…”

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Distinctive features hold a privileged status in the computation of word meaning: Implications for theories of semantic memory.

Cree¹,

McNorgan²,

Masamune³

2006

Journal of Experimental Psychology: Learning, Memory, and Cogni

120

214

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The authors present data from 2 feature verification experiments designed to determine whether distinctive features have a privileged status in the computation of word meaning. They use an attractor-based connectionist model of semantic memory to derive predictions for the experiments. Contrary to central predictions of the conceptual structure account, but consistent with their own model, the authors present empirical evidence that distinctive features of both living and nonliving things do indeed have a privileged role in the computation of word meaning. The authors explain the mechanism through which these effects are produced in their model by presenting an analysis of the weight structure developed in the network during training.Keywords semantic memory; distinctive features; connectionist attractor network; conceptual structure theory The issue of how word meaning is stored in the mind, and computed rapidly when needed, is central both to theories of language comprehension and production and to understanding knowledge deficits in patients with neural impairments. Although we are far from a complete understanding, significant progress has been made since Tulving (1972) first introduced the term "semantic memory." Much of this progress can be attributed to the implementation and development of semantic memory models and the advancement of tools (e.g., semantic feature production norms and word co-occurrence statistics) that enable the rigorous testing of predictions generated from these models.The first models of semantic memory were hierarchical network theory (Collins & Quillian, 1969) and spreading activation theory (Collins & Loftus, 1975). Although both have been extremely influential and have provided predictions for numerous behavioral studies, both have lost favor owing to a number of well-understood and documented flaws (see Rogers & McClelland, 2004, for a recent review). A number of theories of semantic structure have been proposed as alternatives, including the sensory/functional theory (Warrington & Copyright 2006 by the American Psychological Association Correspondence concerning this article should be addressed to George S. Cree, Department of Life Sciences (Psychology), University of Toronto at Scarborough, Toronto, Ontario M1C 1A4, Canada. gcree@utsc.utoronto.ca. McCarthy, 1987), the conceptual structure account (Tyler & Moss, 2001), and the domainspecific hypothesis (Caramazza & Shelton, 1998). Theories of semantic processing have also been proposed, often framed in terms of connectionist networks, and include the work of Plaut and Shallice (1993), Rumelhart and Todd (1993), Rogers and McClelland (2004), and McRae, de Sa, and Seidenberg (1997). Current research focuses on discriminating among these models, integrating the structural and processing components, and developing them to account for behavioral data. NIH Public AccessOne way in which these models are being tested concerns whether concept-feature and feature-feature statistical relations are embedded in the semantic sys...

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“…In general, these models explain how meaning is organized in the mental lexicon and less which mechanisms are used to access meaning. Classical examples of semantic models are the hierarchical network model, 91 the semantic feature model, 92 the spreading activation model, 93 and the ACT model. 94 The question of whether phonological representations of words are tantamount to semantic representations is also a matter of debate in the field of spoken-word recognition.…”

Section: Discussionmentioning

confidence: 99%

Models of spoken‐word recognition

Weber

Scharenborg

2012

WIRES Cognitive Science

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All words of the languages we know are stored in the mental lexicon. Psycholinguistic models describe in which format lexical knowledge is stored and how it is accessed when needed for language use. The present article summarizes key findings in spoken‐word recognition by humans and describes how models of spoken‐word recognition account for them. Although current models of spoken‐word recognition differ considerably in the details of implementation, there is general consensus among them on at least three aspects: multiple word candidates are activated in parallel as a word is being heard, activation of word candidates varies with the degree of match between the speech signal and stored lexical representations, and activated candidate words compete for recognition. No consensus has been reached on other aspects such as the flow of information between different processing levels, and the format of stored prelexical and lexical representations. WIREs Cogn Sci 2012, 3:387–401. doi: 10.1002/wcs.1178This article is categorized under: Linguistics > Computational Models of Language

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Retrieval time from semantic memory

Cited by 2,456 publications

References 4 publications

The company that words keep: comparing the statistical structure of child- versus adult-directed language

The company that words keep: comparing the statistical structure of child- versus adult-directed language

Distinctive features hold a privileged status in the computation of word meaning: Implications for theories of semantic memory.

Models of spoken‐word recognition

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