Identifying Text Objects Based on Expansion

K. Ohkubo, T. Miura
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Abstract

In this investigation, we propose a sophisticated approach to identify items in several dictionaries for the purpose of integration. To identity synonymous words efficiently, we discuss IR approach based on vector space modeling to sentences in item explanations, without any knowledge of grammatical analysis or any other NLP analysis. We show the usefulness by some experimental results.
基于扩展的文本对象识别
在这项研究中,我们提出了一种复杂的方法来识别几个字典中的项目,以实现整合。为了有效地识别同义词,我们讨论了基于向量空间建模的IR方法,在没有任何语法分析或任何其他NLP分析知识的情况下,对项目解释中的句子进行建模。通过一些实验结果证明了该方法的有效性。
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