Improving the identification of verbs

ACM-SE 35 Pub Date : 1997-04-02 DOI:10.1145/2817460.2817470
Lynellen D. S. Perry
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引用次数: 1

Abstract

In automatically assigning part-of-speech tags to scientific text, we find a high error rate when tagging main verbs. To reduce the occurrence of this serious error, we have created a neural network to search for main verbs that have been mis-tagged by a rule-based tagger. In this paper we describe our efforts to evolve the connection weights for the neural network, and to fractally configure another neural network for the same task.
提高对动词的识别能力
在科技文本词性标签自动分配中,我们发现标注主要动词的错误率很高。为了减少这种严重错误的发生,我们创建了一个神经网络来搜索被基于规则的标注器错误标注的主要动词。在本文中,我们描述了我们的努力,进化神经网络的连接权,并分形配置另一个神经网络来完成相同的任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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