基于N-gram和KNN分类器的情感分析方法

Sumandeep Kaur, Geeta Sikka, L. Awasthi
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引用次数: 5

摘要

情感分析是一种分析任何文本单元的积极、消极和中性方面的方法。在过去的几年里,许多技术被设计用于twitter数据的情感分析。本文在前人情感分析研究的基础上,提出了一种新的twitter数据情感分析方法。该方法是特征提取和分类技术的结合。采用N-gram算法进行特征提取,采用KNN分类器将输入数据分为正类、负类和中性类。为了验证该系统的有效性,从查全率、查全率和查准率三个方面进行了性能分析。实验结果表明,与现有的基于支持向量机分类器的系统相比,该系统具有良好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sentiment Analysis Approach Based on N-gram and KNN Classifier
Sentiment analysis is the approach which is designed to analyze positive, negative and neutral aspects of any text unit. In the past years, many techniques were designed for the sentiment analysis of twitter data. Based on the previous study about sentiment analysis, a novel approach is presented in this research paper for the sentiment analysis of twitter data. The proposed approach is the combination of feature extraction and classification techniques. N-gram algorithm is applied for the feature extraction and KNN classifier is applied to classify input data into positive, negative and neutral classes. To validate the proposed system, performance is analyzed in terms of precision, recall and accuracy. The results of the experiment of proposed system show that it performs well as compared to the existing system which is based on SVM classifier.
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