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Utilizing CNN, RNN, HAN, and RMDL with embeddings like FastText, replacing Word2Vec (93.10% accuracy) with FastText (98.65%) improved sentiment analysis accuracy by 5.55%. This enhanced model comprehension of hotel reviews, supporting customer decision-making.
This program showcases a practical application of heuristic concepts, self adjusting data structures, and sorting algorithms by solving a callous twist on the infamous traveling salesman problem.