A framework of a mechanical translation between Japanese and English by analogy principle
Proc. of the international NATO symposium on Artificial and human intelligence
Communications of the ACM - Special issue on parallelism
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NEC's machine translation system "PIVOT" provides analysis editing functions. The user can interactively correct errors in analysis results, such as dependency and case. However, without a learning mechanism, the user must correct similar dependency errors several times. We discuss the learning mechanism to utilize dependency and case information specified by the user. We compare four types of matching methods by simulation and show non-restricted best matching is the most effective.