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What is Optimized Framework for Sentiment Analysis about?

The document presents an optimized crossover framework for social media sentiment analysis, utilizing deep learning techniques. It outlines a four-phase approach involving pre-processing, feature extraction, feature selection, and sentiment classification, with a focus on enhancing classification accuracy through the Self Improved Honey Badger Algorithm (SI-HBA). The proposed model aims to efficiently classify sentiments as positive, negative, or neutral by integrating optimized Bi-LSTM and Deep Belief Netw

Author

sssamant

Language

EN