使用隐马尔可夫模型的马拉雅拉姆语POS标注器

2019 International Conference on Smart Systems and Inventive Technology (ICSSIT) Pub Date : 2019-11-01 DOI:10.1109/ICSSIT46314.2019.8987786

Sindhya K. Nambiar, Antony Leons, Soniya Jose, Arunsree

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引用次数: 4

摘要

NLP应用程序使用词性标注作为预处理步骤。为了使词性标注准确，人们探索了各种技术。但在印度语言方面，还没有做太多的工作。本文介绍了结合隐马尔可夫模型构建词性标注器。在监督学习方法中，使用马拉雅拉姆语已经标记的句子来构建隐马尔可夫模型。

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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POS Tagger for Malayalam using Hidden Markov Model

The NLP applications uses the parts of speech tagging as the preprocessing step. For making POS tagging accurate, various techniques have been explored. But in Indian languages, not much work has been done. This paper describes Part of Speech Tagger by incorporating Hidden Markov Model is built. Supervised learning approach is implemented in which, already tagged sentences in Malayalam is used to build Hidden Markov Model.

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2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)

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