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The current Natural Language Processing (NLP) means is chiefly grounded on the principle of language rules' description pattern, which lacks comprehensive semantic representation capability, and therefore it can not efficiently process the real texts in the layer of semantic meaning. This paper presents a semantic representation approach based on term connection samples. This method promotes the idea of describing fundamental language samples, and can analyze comprehensive semantic representations.... The current Natural Language Processing (NLP) means is chiefly grounded on the principle of language rules' description pattern, which lacks comprehensive semantic representation capability, and therefore it can not efficiently process the real texts in the layer of semantic meaning. This paper presents a semantic representation approach based on term connection samples. This method promotes the idea of describing fundamental language samples, and can analyze comprehensive semantic representations. So far it has been applied in project CAPC (Computer Aided Poetry Composing) funded by the Chinese Natural Science Foundation. 现有自然语言处理方法主要采取描述语言规律的基本思路,缺乏全面的语义表示能力,因此不能从语义层面有效处理各种类型的真实文本。笔者提出一种基于词联接实例的语义表示方法。该方法采取描述底层语言实例的基本思路,具有全面的语义表示能力,目前已应用于国家自然科学基金资助的"计算机辅助文学艺术创作研究———诗词曲联"项目。
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