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Handbook of Multimedia Information Security: Techniques and ApplicationsAnalysis of Streaming Data Using Big Data and Hybrid Machine Learning Approach

Handbook of Multimedia Information Security: Techniques and Applications: Analysis of Streaming... [A lot of data is generated from multiple sources. This data contains many hidden patterns and information. Data from Social Networks mostly contains opinions. These opinions can be mined to lead various extractions from organizational point of view. In this chapter, the authors are storing the Twitter Streaming Data into HDFS of Hadoop by using Flume and then extracting with Apache Hive. Later, Machine Learning classification algorithms are applied to decode the sentiment in this data. A novel approach based on hybrid Naïve Bayes and Decision Tree Algorithms are used to enhance the performance of sentiment analysis of streaming twitter data. Naïve Bayes is a powerful and simple classification algorithm. But it assumes independence of features. So, Decision Tree has been used in conjunction with it to get more accurate result. Decision Tree has some rules. Algorithms are combined using Averaging Rule. The implemented research approach achieved an accuracy of 86.44% in comparison to 81.11% for Naïve Bayes Classifier.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Handbook of Multimedia Information Security: Techniques and ApplicationsAnalysis of Streaming Data Using Big Data and Hybrid Machine Learning Approach

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References (32)

Publisher
Springer International Publishing
Copyright
© Springer Nature Switzerland AG 2019
ISBN
978-3-030-15886-6
Pages
629 –643
DOI
10.1007/978-3-030-15887-3_30
Publisher site
See Chapter on Publisher Site

Abstract

[A lot of data is generated from multiple sources. This data contains many hidden patterns and information. Data from Social Networks mostly contains opinions. These opinions can be mined to lead various extractions from organizational point of view. In this chapter, the authors are storing the Twitter Streaming Data into HDFS of Hadoop by using Flume and then extracting with Apache Hive. Later, Machine Learning classification algorithms are applied to decode the sentiment in this data. A novel approach based on hybrid Naïve Bayes and Decision Tree Algorithms are used to enhance the performance of sentiment analysis of streaming twitter data. Naïve Bayes is a powerful and simple classification algorithm. But it assumes independence of features. So, Decision Tree has been used in conjunction with it to get more accurate result. Decision Tree has some rules. Algorithms are combined using Averaging Rule. The implemented research approach achieved an accuracy of 86.44% in comparison to 81.11% for Naïve Bayes Classifier.]

Published: Jul 20, 2019

Keywords: Big Data; Sentiment; Multimedia; Decision Tree; Naïve Bayes; Machine learning

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