Arabic Script Documents Language Identifications Using Fuzzy ART

A. Selamat, Choon-Ching Ng
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引用次数: 10

Abstract

The volume of information available on the internet, intranet, digital libraries and newsgroup has increased dramatically in recent years. Therefore, there is a growing interest in helping user better find, filter, and manage these resources. Language identification is the first step of understanding text documents which is written in. It is usually a module within multilingual application. In this paper, we introduce language identification of Arabic script documents by letter frequency. Technique used for identification is fuzzy adaptive resonance theory (ART), which is belong to the neural network architectures that perform incremental unsupervised learning. Arabic script documents such as Arabic, Persian and Urdu were used for performing language identification. From the experiments, we have found that fuzzy ART is particularly promising in terms of accuracy on language identification.
使用模糊ART的阿拉伯文字文档语言识别
近年来,互联网、内部网、数字图书馆和新闻组上的信息量急剧增加。因此,人们对帮助用户更好地查找、过滤和管理这些资源越来越感兴趣。语言识别是理解文本文档的第一步。它通常是多语言应用程序中的一个模块。本文介绍了利用字母频率对阿拉伯文字文件进行语言识别的方法。用于识别的技术是模糊自适应共振理论(ART),这是一种执行增量无监督学习的神经网络结构。阿拉伯文字文件,如阿拉伯语、波斯语和乌尔都语被用来进行语言识别。从实验中,我们发现模糊ART在语言识别的准确性方面特别有前景。
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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