Web based machine learning for language identification and translation

Ş. Sağiroğlu, U. Yavanoglu, Esra Nergis Guven
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引用次数: 17

Abstract

Language identification is an important task for Web information retrieval services. This paper presents the implementation of a platform for language identification in multi-lingual documents on Web. The platform consists of five modules to achieve the tasks automatically. Furthermore, artificial neural networks were used for the identification of languages in multi-lingual documents. Results for six languages including Turkish, French, Italian, Danish and Deutsch are present. The major benefit of the approach is that the ANN based language identification system could meet the expectations in real-time language identification accuracy with the help of a developed system. Experiments have shown that system achieves the tasks in high accuracy in discriminating different languages and converting them other languages on Web pages.
基于Web的语言识别和翻译机器学习
语言识别是Web信息检索服务的一项重要任务。本文介绍了一个基于Web的多语种文档语言识别平台的实现。该平台由五个模块组成,可自动完成任务。此外,还利用人工神经网络对多语种文档中的语言进行识别。目前有包括土耳其语、法语、意大利语、丹麦语和德语在内的六种语言的结果。该方法的主要优点是基于人工神经网络的语言识别系统可以在开发的系统的帮助下满足实时语言识别精度的期望。实验表明,该系统在网页上对不同语言进行识别和转换,达到了较高的准确率。
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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