Abstract
Connectionism is a relatively new approach to language processing and has comparatively few standard methods for syntax analysis and parsing relative to classical symbolic methods. The interest in connectionism has arisen due to its learning capability, tolerance to noisy input, and ability to generalize from previous examples. Classical rule-based techniques are well understood but tend to be intolerant of minor variations that do not strictly adhere to predefined rules.
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Tepper, J.A., Powell, H., Palmer-Brown, D. (1995). Integrating Symbolic and Subsymbolic Architectures for Parsing Arithmetic Expressions and Natural Language Sentences. In: Kappen, B., Gielen, S. (eds) Neural Networks: Artificial Intelligence and Industrial Applications. Springer, London. https://doi.org/10.1007/978-1-4471-3087-1_16
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DOI: https://doi.org/10.1007/978-1-4471-3087-1_16
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