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Title: Sentiment Analysis Using Customizable Naive Bayes Classifier
Authors: Pasia, Alyssa Jayne
Keywords: Sentiment analysis
Opinion mining
Text classification
Naive Bayes classification
Bayes rule
Issue Date: May-2018
Abstract: Huge amount of data are available on the internet. Due to this, there is an increasing interest in automatically obtaining valuable information from these data using Sentiment Analysis. A lot of methods and datasets are used to build models for classifying. This project aims to develop a system that lets the user decide on what datasets and preprocessing techniques are to be used on a Naive Bayes Classi er model.
Appears in Collections:Computer Science SP

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