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The sentiment-summary module generates summaries from larger bodies of text considering sentence-level sentiment. Multiple summarization algorithms and sentiment analysis engines are supported.
This project is a corporate partnership with the online bookstore platform 'YES24', where we collect data from various platforms such as YouTube to analyze the latest trends and develop a service that recommends books matching these trends.
This repository contains various models for text summarization tasks. Each model has a separate directory containing the implementation code, pretrained weights, and a Jupyter notebook for testing the model on sample input texts. Feel free to use these models for your own text summarization tasks or to experiment with them further.