RBIPA: An Algorithm for Iterative Stemming of Tamil Language Texts

V. Indumathi, S. SanthanaMegala
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引用次数: 0

Abstract

Cyberbullying is currently one of the most important research fields. The majority of researchers have contributed to research on bully text identification in English texts or comments, due to the scarcity of data; analyzing Tamil textstemming is frequently a tedious job. Tamil is a morphologically diverse and agglutinative language. The creation of a Tamil stemmer is not an easy undertaking. After examining the major difficulties encountered, proposed the rule-based iterative preprocessing algorithm (RBIPA). In this attempt, Tamil morphemes and lemmas were extracted using the suffix stripping technique and a supervised machine learning algorithm for classify the word based for pronouns and proper nouns. The novelty of proposed system is developing a preprocessing algorithm for iterative stemming; lemmatize process to discovering exact words from the Tamil Language comments. RBIPA shows 84.96% of accuracy in the given Test Dataset which hasa total of 13000 words.
泰米尔语文本的迭代词干提取算法
网络欺凌是目前最重要的研究领域之一。由于数据的缺乏,大多数研究人员对英语文本或评论中的欺凌文本识别做出了贡献;分析泰米尔文本词干通常是一项乏味的工作。泰米尔语是一种形态多样且具有黏性的语言。创建一个泰米尔语系统并不是一件容易的事情。在分析遇到的主要困难后,提出了基于规则的迭代预处理算法(RBIPA)。在这次尝试中,使用后缀剥离技术和监督机器学习算法提取泰米尔语素和引理,并根据代词和专有名词对单词进行分类。该系统的新颖之处在于开发了迭代词干提取的预处理算法;从泰米尔语的评论中发现准确单词的词序化过程。RBIPA在给定的13000个单词的测试数据集中显示出84.96%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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