Random Forest and Support Vector Machine based Hybrid Approach to Sentiment Analysis-Reference-Cited by-同舟云学术

Random Forest and Support Vector Machine based Hybrid Approach to Sentiment Analysis

Published:2018 Issue: Volume:127 Page:511-520
ISSN:1877-0509
Container-title:Procedia Computer Science
language:en
Short-container-title:Procedia Computer Science

Author:

Al Amrani Yassine,Lazaar Mohamed,El Kadiri Kamal Eddine

Publisher

Elsevier BV

Subject

General Engineering

Reference17 articles.

1. “Sentiment analysis using weka,”;Umadevi;IJETT International Journal of Engineering Trends and Technology,2014

2. “Sentiment analysis: A combined approach,”;Prabowo;Journal of Informetrics,2015

3. “Sentiment analysis and opinion mining,”;Liu;Synthesis Lectures on Human Language Technologies,2012

4. “Analysis of different approaches to Sentence-Level Sentiment Classification,”;Jagtap;International Journal of Scientific Engineering and Technology,2013

5. “Ensemble of feature sets and classification algorithms for sentiment classification,”;Xia;Information Sciences,2011

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