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Parallel processing is not only a general topic of interest for computer scientists and researchers in artificial intelligence, but it is gaining more and more attention in the community of scientists studying natural language and its processing (computational linguists, AI researchers, psychologists). The growing need to integrate large divergent bodies of knowledge in natural language processing applications, or the belief that massively parallel systems are the only ones capable of handling the complexities and subtleties of natural language, are just two examples of the reasons for this increasing interest. This volume offers 13 contributions by scientists from the fields of computer, artificial intelligence, and computational linguistics. The chapters provide an extensive introduction to the field, as well as articles that deal with both coarse-grained (symbolic) and fine-grained (connectionist) approaches. Along another axis, theoretical and methodological, as well as empirical and implementational issues are treated, and both language analysis and language generation are covered.
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Parallel processing is not only a general topic of interest for computer scientists and researchers in artificial intelligence, but it is gaining more and more attention in the community of scientists studying natural language and its processing (computational linguists, AI researchers, psychologists). The growing need to integrate large divergent bodies of knowledge in natural language processing applications, or the belief that massively parallel systems are the only ones capable of handling the complexities and subtleties of natural language, are just two examples of the reasons for this increasing interest.
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