Intelligent Hybrid Feature Selection for Textual Sentiment Classification

Intelligent Hybrid Feature Selection for Textual Sentiment Classification

Sentiment Analysis (SA) aims to extract useful information from online Unstructured User-Generated Contents (UUGC) and classify them into positive and negative classes. State-of-the-art techniques for SA suffer a high dimensional feature space because of noisy and irrelevant features from the UUGC....

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Bibliographic Details
Main Authors: Jawad Khan, Aftab Alam, Youngmoon Lee
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Sentiment classification
hybrid feature selection
ensemble learning
linguistic semantic rules
wide coverage sentiment lexicons
natural language processing
Online Access:https://ieeexplore.ieee.org/document/9564065/

Internet

https://ieeexplore.ieee.org/document/9564065/

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