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Applying Parallel Processing to Natural-Language Processing
February 1994 (vol. 9 no. 1)
pp. 36-44

Massively parallel computers offer not only improved speed but also a new perspective on computer vision, production systems, neural networks, and other AI applications. However, not much work has been done to apply parallel processing to natural-language processing, even though most sequential natural-language systems slow down as knowledge bases grow to realistic sizes and as linguistic features are added to handle special cases. To demonstrate the potential of parallel systems for natural-language processing, we selected an inherently parallel knowledge representation and reasoning method (marker-passing in a semantic network) and then developed a natural-language processor based on it. We implemented the memory-based parsing system/spl minus/called Parallel/spl minus/on a marker-passing parallel computer especially designed for natural-language processing.

Citation:
Minhwa Chung, Dan Moldevan, "Applying Parallel Processing to Natural-Language Processing," IEEE Intelligent Systems, vol. 9, no. 1, pp. 36-44, Feb. 1994, doi:10.1109/64.295133
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