基于神经网络的阿拉伯语三音节词根提取

Hasan Muaidi Al-Serhan, A. Ayesh
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引用次数: 25

摘要

许多现有的阿拉伯语词干提取算法使用大量的规则集。在许多情况下,它们引用模式和根的查找表。这需要很大的存储空间和访问信息的时间。提出了一种基于神经网络的阿拉伯语词干提取方法。该方法试图利用反向传播神经网络(BPNN)来挖掘字符之间的数值关系。利用神经网络提取阿拉伯语词干的系统在文献中尚未发现
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Triliteral Word Roots Extraction Using Neural Network For Arabic
Many of existing Arabic stemming algorithms use a large set of rules. In many cases, they refer to a lookup table of patterns and roots. This requires a large storage space, and time to access the information. A novel neural network based approach for stemming Arabic words is proposed in this paper. This approach attempts to exploit numerical relations between characters by using backpropagation neural network (BPNN). No such system in literature can be found that uses neural network to extract the stemming of Arabic words
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