The project provides a robust, end-to-end Python pipeline for identifying, analyzing, and understanding the evolution of narratives within large-scale longitudinal text corpora. This project provides ...
Abstract: With the progress of science and technology, a large number of scientific papers are published every year. Faced with such large data, identifying high-value research and hot research ...
Abstract: Dynamic topic models are techniques used to uncover latent topic evolution from large-scale sequential text. Existing models typically encode documents as word sequences. However, due to the ...
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