Further evidence for feature correlations in semantic memory
Further evidence for feature correlations in semantic memory
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DOI：
10.1037/h0087323
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发表时间：
1999-12-01
影响因子：
1.3
通讯作者：
De Sa, VR
中科院分区：
文献类型：
--
作者：
McRae, K;Cree, GS;De Sa, VR
特征关联在语义记忆中的作用是概念表征中的一个核心问题。在两个版本的特征验证任务中，如果一个特征（<是多汁的>）与一个概念（葡萄柚）的其他特征具有强相关性，而不是弱相关性，那么参与者可以更快地验证这个特征（<是多汁的>）是这个概念（葡萄柚）的一部分。当首先提出概念与功能时，可以发现功能相关性与SOA之间的对比交互。词义的吸引子网络模型自然地学习并使用特征相关性来预测这些相互作用。这项研究提供了进一步的证据，表明语义记忆包括隐式学习的特征关系的统计知识，而不是像扩散激活网络这样的理论，其中特征相关性不起作用。
The role of feature correlations in semantic memory is a central issue in conceptual representation. In two versions of the feature verification task, participants were faster to verify that a feature (< is juicy >) is part of a concept (grapefruit) if it is strongly rather than weakly intercorrelated with the other features of that concept. Contrasting interactions between feature correlations and SOA were found when the concept versus the feature was presented first. An attractor network model of word meaning that naturally learns and uses feature correlations predicted those interactions. This research provides further evidence that semantic memory includes implicitly learned statistical knowledge of feature relationships, in contrast to theories such as spreading activation networks, in which feature correlations play no role.