Abstract
The concept of Dynamic Neural Networks (DNN) is a new approach within the Neural Network paradigm, which is based on the dynamic construction of Neural Networks during the processing of an input. The DNN methodology has been employed in the Hybrid Connectionist Parsing (HCP) approach, which comprises an incremental, on-line generation of a Neural Network parse tree. The HCP ensures an adequate representation and processing of recursively defined structures, like grammar-based languages. In this paper, we describe the general principles of the HCP method and some of its specific Neural Network features. We outline and discuss the use of the HCP method with respect to parallel processing of ambiguous structures, and robust parsing of extra-grammatical inputs in the context of spoken language parsing.
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Kemke, C. (2002). A Constructive Approach to Parsing with Neural Networks — The Hybrid Connectionist Parsing Method. In: Cohen, R., Spencer, B. (eds) Advances in Artificial Intelligence. Canadian AI 2002. Lecture Notes in Computer Science(), vol 2338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47922-8_26
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DOI: https://doi.org/10.1007/3-540-47922-8_26
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