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Transformer-based models like BERT (Bidirectional Encoder Representations from Transformers) are highly effective in sentiment analysis due to their ability to understand context and semantics in both directions of a sentence. Unlike traditional models, BERT processes the entire text bidirectionally, capturing subtle nuances, such as sarcasm, negations, or contextual modifiers, that significantly impact sentiment. For example, in a sentence like "The service was not bad," BERT accurately identifies the positive sentiment by considering the negation. Additionally, its pre-training on massive datasets and fine-tuning for specific tasks make it robust for domain-specific sentiment analysis, offering unparalleled accuracy compared to other NLP techniques. Why Other Options Are Incorrect:
What resources is a manger mainly concerned with?
Soil structural units having horizontal axis much longer than vertical axis. Such type of soil structure is known as
Which of the following is NOT an element of the marketing mix?
Choose the correct statement.
What is the initiative introduced in 2023 that focuses on reducing fertilizer consumption and creating awareness?
What will be the colour reaction with iodine of a plant kept in dark for few days?
Name the vegetative propagation techniques where the plant part to be cut is rooted before it is completely cut away from the parent plant.
In the preparation of audio-visual aids, the principle of ‘A’, ‘B’, ‘C’ signifies:
Which wheat rust is known as a killer disease?
The treatment of seeds with rhizobium culture and fungicides is done in: