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Aspects of Automatic Text Analysis pp 363–386Cite as

Neural Networks, Fuzzy Models and Dynamic Logic

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 209))

Abstract

The paper discusses possible relationships between computational intelligence, known mechanisms of the mind, semiotics, and computational linguistics. Mathematical mechanisms of concepts, emotions, and goals are described as a part of information processing in the mind and are related to language and thought processes in which an event (signals from surrounding world, text corpus, or inside the mind) is understood as a concept. Previous attempts in artificial intelligence at describing thought processes are briefly reviewed and their fundamental (mathematical) limitations are analyzed. The role of emotional signals in overcoming these past limitations is emphasized. The paper describes mathematical mechanisms of concepts applicable to sensory signals and linguistics; they are based on measures of similarities between models and signals. Linguistic similarities are discussed that can utilize various structures and rules proposed in computational linguistic literature. A hierarchical structure of the proposed method is capable of learning and recognizing concepts from textual data, from the level of words and up to sentences, groups of sentences, and towards large bodies of text. I briefly discuss a role of concepts as a mechanism unifying thinking and language and their possible role in language acquisition. A thought process is related to semiotic notions of signs and symbols. It is further related to understanding, imagination, intuition, and other processes in the mind. The paper briefly discusses relationships between the mind and brain and applications to understanding-based search engines.

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Authors and Affiliations

  1. Air Force Research Lab, USA

    Leonid I. Perlovsky

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  1. Leonid I. Perlovsky
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© 2007 Springer

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Perlovsky, L.I. (2007). Neural Networks, Fuzzy Models and Dynamic Logic. In: Aspects of Automatic Text Analysis. Studies in Fuzziness and Soft Computing, vol 209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37522-7_17

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  • DOI: https://doi.org/10.1007/978-3-540-37522-7_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-37520-3

  • Online ISBN: 978-3-540-37522-7

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