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首页> 外文期刊>Journal of computer sciences >Integrating a Lexicon Based Approach and K Nearest Neighbour for Malay Sentiment Analysis | Science Publications
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Integrating a Lexicon Based Approach and K Nearest Neighbour for Malay Sentiment Analysis | Science Publications

机译:集成基于词汇的方法和K最近邻,用于马来语情感分析|英特尔®开发人员专区科学出版物

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> >Sentiment analysis or opinion mining refers to the automatic extraction of sentiments from a natural language text. Although many studies focusing on sentiment analysis have been conducted, there remains a limited amount of studies that focus on sentiment analysis in the Malay language. In this article, a new approach for automatic sentiment analysis of Malay movie reviews is proposed, implemented and evaluated. In contrast to most studies that focus on supervised or unsupervised machine learning approaches, this research aims to propose a new model for Malay sentiment analysis based on a combination of both approaches. We used sentiment lexicons in the new model to generate a new set of features to train a k-Nearest Neighbour (k-NN) classifier. We further illustrated that our hybrid method outperforms the state of-the-art unigram baseline.
机译: > >情感分析或观点挖掘是指从自然语言文本中自动提取情感。尽管已经进行了许多关注情绪分析的研究,但是仍然有少量研究关注马来语的情绪分析。在本文中,提出,实施和评估了一种新的自动分析马来电影评论情绪的方法。与大多数专注于有监督或无监督机器学习方法的研究相比,本研究旨在基于两种方法的组合提出一种新的马来情绪分析模型。我们在新模型中使用了情感词典,以生成一组新特征来训练k最近邻(k-NN)分类器。我们进一步说明,我们的混合方法优于最新的unigram基线。

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