Kohei Kurihara

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This paper describes Japanese textual entailment recognition systems for NTCIR-10 RITE2. The tasks that we participated in are the Japanese BC subtask and the Ex-amBC subtask. Our methods are based on some machine learning techniques with surface level, syntax and semantic features. We use two ontologies, the Japanese WordNet and Nihongo-Goi-Taikei, and(More)
In spite of wide-ranging previous studies on synthetic macrocycles, installation of open-close functions into the frameworks remains a knotty challenge. Here we present a new polyaromatic macrocycle capable of switching between open and closed forms in response to external stimuli, base and acid. The macrocycle, prepared in three steps, has a well-defined(More)
In this paper, we propose a method for extracting trouble information from Twitter. One useful approach is based on machine learning techniques such as SVMs. However, trouble information is a fraction of a percent of all tweets on Twitter. In general, imbalanced distribution is not suitable for machine learning techniques to generate a classifier. Another(More)
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