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  1. A Context Maintenance and Retrieval Model of Organizational Processes in Free Recall.Sean M. Polyn, Kenneth A. Norman & Michael J. Kahana - 2009 - Psychological Review 116 (1):129-156.
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  • Putting Short-Term Memory Into Context: Reply to Usher, Davelaar, Haarmann, and Goshen-Gottstein.Michael J. Kahana, Per B. Sederberg & Marc W. Howard - 2008 - Psychological Review 115 (4):1119-1125.
  • Short-Term Memory for Serial Order: A Recurrent Neural Network Model.Matthew M. Botvinick & David C. Plaut - 2006 - Psychological Review 113 (2):201-233.
  • Multiply-Constrained Semantic Search in the Remote Associates Test.Kevin A. Smith, David E. Huber & Edward Vul - 2013 - Cognition 128 (1):64-75.
  • A Model for Stochastic Drift in Memory Strength to Account for Judgments of Learning.Sverker Sikström & Fredrik Jönsson - 2005 - Psychological Review 112 (4):932-950.
  • The Episodic Nature of Experience: A Dynamical Systems Analysis.Sreekumar Vishnu, Dennis Simon & Doxas Isidoros - 2017 - Cognitive Science 41 (5):1377-1393.
    Context is an important construct in many domains of cognition, including learning, memory, and emotion. We used dynamical systems methods to demonstrate the episodic nature of experience by showing a natural separation between the scales over which within-context and between-context relationships operate. To do this, we represented an individual's emails extending over about 5 years in a high-dimensional semantic space and computed the dimensionalities of the subspaces occupied by these emails. Personal discourse has a two-scaled geometry with smaller within-context dimensionalities (...)
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  • A Large‐Scale Analysis of Variance in Written Language.Brendan T. Johns & Randall K. Jamieson - 2018 - Cognitive Science 42 (4):1360-1374.
    The collection of very large text sources has revolutionized the study of natural language, leading to the development of several models of language learning and distributional semantics that extract sophisticated semantic representations of words based on the statistical redundancies contained within natural language. The models treat knowledge as an interaction of processing mechanisms and the structure of language experience. But language experience is often treated agnostically. We report a distributional semantic analysis that shows written language in fiction books varies appreciably (...)
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  • Context Noise and Item Noise Jointly Determine Recognition Memory: A Comment on Dennis and Humphreys.Amy H. Criss & Richard M. Shiffrin - 2004 - Psychological Review 111 (3):800-807.
  • Constructing Semantic Representations From a Gradually Changing Representation of Temporal Context.Marc W. Howard, Karthik H. Shankar & Udaya K. K. Jagadisan - 2011 - Topics in Cognitive Science 3 (1):48-73.
    Computational models of semantic memory exploit information about co-occurrences of words in naturally occurring text to extract information about the meaning of the words that are present in the language. Such models implicitly specify a representation of temporal context. Depending on the model, words are said to have occurred in the same context if they are presented within a moving window, within the same sentence, or within the same document. The temporal context model (TCM), which specifies a particular definition of (...)
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