Enhancing sentiment classification performance using hybrid Query Expansion Ranking and Binary Particle Swarm Optimization with Adaptive Inertia Weights
Machine learning-based sentiment classification is the best-performing method to understand public sentiment. However, the method has some problems, such as noisy features and high-dimensional feature space which affect the sentiment classification performance. To address the problems, this paper pr...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Korean Institute of Communication Sciences
2021
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| Subjects: | |
| Online Access: | https://repository.ugm.ac.id/278935/1/Prastyo_TK.pdf |