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      Extracting semantic representations from word co-occurrence statistics: a computational study.

      Behavior Research Methods

      Data Interpretation, Statistical, Vocabulary, Semantics, Models, Psychological, Humans

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          Abstract

          The idea that at least some aspects of word meaning can be induced from patterns of word co-occurrence is becoming increasingly popular. However, there is less agreement about the precise computations involved, and the appropriate tests to distinguish between the various possibilities. It is important that the effect of the relevant design choices and parameter values are understood if psychological models using these methods are to be reliably evaluated and compared. In this article, we present a systematic exploration of the principal computational possibilities for formulating and validating representations of word meanings from word co-occurrence statistics. We find that, once we have identified the best procedures, a very simple approach is surprisingly successful and robust over a range of psychologically relevant evaluation measures.

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          Most cited references 16

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          Self-Organizing Maps

           Teuvo Kohonen (1997)
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            Is Open Access

            The Symbol Grounding Problem

             Stevan Harnad (1999)
            How can the semantic interpretation of a formal symbol system be made intrinsic to the system, rather than just parasitic on the meanings in our heads? How can the meanings of the meaningless symbol tokens, manipulated solely on the basis of their (arbitrary) shapes, be grounded in anything but other meaningless symbols? The problem is analogous to trying to learn Chinese from a Chinese/Chinese dictionary alone. A candidate solution is sketched: Symbolic representations must be grounded bottom-up in nonsymbolic representations of two kinds: (1) "iconic representations," which are analogs of the proximal sensory projections of distal objects and events, and (2) "categorical representations," which are learned and innate feature-detectors that pick out the invariant features of object and event categories from their sensory projections. Elementary symbols are the names of these object and event categories, assigned on the basis of their (nonsymbolic) categorical representations. Higher-order (3) "symbolic representations," grounded in these elementary symbols, consist of symbol strings describing category membership relations (e.g., "An X is a Y that is Z").
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              Category norms of verbal items in 56 categories A replication and extension of the Connecticut category norms.

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                Author and article information

                Journal
                17958162

                Chemistry

                Data Interpretation, Statistical, Vocabulary, Semantics, Models, Psychological, Humans

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