A Memory-Based Alternative for Connectionist Shift-Reduce Parsing
نویسنده
چکیده
In this paper we present memory-based learning (mbl) as a psychologically plausible model of natural language processing. Mbl shows a state-of-the-art performance on real-world language tasks, such as word pronunciation , word sense disambiguation and parsing. We compare mbl to a neural network model, SardSrn (May-berry & Miikkulainen, 1999) on a parsing task, and we show that mbl has a better generalisation accuracy on the test set. Mbl has a solid foundation in the psychological literature within theories on human categorisa-tion and reasoning. We argue that mbl is an alternative psychologically plausible model for human parsing, next to neural network models.
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