Hybrid recommendation system of intelligent captioning using deep learning networks

Abstract

This research introduces a hybrid recommendation system through sentiment analysis for Bangla long textual sentences. Social media, as a vast source of opinions, can be harnessed through sentiment analysis using deep learning techniques, overcoming language barriers and improving recommendation systems. The paper addresses challenges in Bangla sentiment analysis, such as the scarcity of datasets and linguistic nuances, proposing a model that combines LSTM, Bi-LSTM, and CNN for optimized text sequence classification. The study explores six neural network models (ANN, CNN, LSTM,Bi-LSTM,BERT,RCNN) overcoming obstacles in dataset quality and distribution. Challenges in data collection, model selection, and computational resources are discussed. The paper concludes with the acknowledgment of the evolving frontier of sentiment analysis in Bangla text, emphasizing the transformative potential with continued efforts to expand datasets and refine algorithms.