Naoyuki Tokuda


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A Differential LSI Method for Document Classification
Liang Chen | Naoyuki Tokuda | Akira Nagai
Proceedings of the Sixth International Workshop on Information Retrieval with Asian Languages

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A Patent Document Retrieval System Addressing Both Semantic and Syntactic Properties
Liang Chen | Naoyuki Tokuda | Hisahiro Adachi
Proceedings of the ACL-2003 Workshop on Patent Corpus Processing


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A new diagnostic system for J-E translation ILTS by global matching algorithm and POST parser
Liang Chen | Naoyuki Tokuda
Proceedings of Machine Translation Summit VII

A new diagnostic system has been developed for an interactive template-structured intelligent language tutoring system (ILTS) for Japanese-English translation where an efficient heaviest common sequence (HCS) matching algorithm and a ‘part-of-speech tagged (POST) parser’ play a key role. This is implemented by exploiting the system template which consists of a complex transition networks comprising both model (correct) translations and many typical erroneous translations characteristic of nonnative beginners all collected and extracted from translations of about 200 monitors. By selecting, from among many candidates’ paths in the system template, a path having a HCS with the student’s input translation as a best matched sentence, the template structure of the diagnostic system allows the potentially complicated bug finding processes in natural language to be implemented by a much simpler and efficient HCS string matching algorithm [20]. To improve the precision of a parser, we have developed a ‘probabilistic POST parser’ where we have eliminated ambiguity in part-of-speeches by manually pre-assigning POS tags to all words in potentially correct paths of the template. Combining the templatebased diagnostic system and the parser, we found that the ILTS is capable of providing most adequate diagnostic messages and a tutoring strategy with appropriate comments after analyzing the keyed-in translated sentences from students.