Prototype of a system for news-based market intelligence at the Port of Santos
Keywords:
Text Summarization, Natural Language Processing, Market intelligence, Port NewsAbstract
This article proposes an innovative method for summarizing texts related to port news, performance indicators, and products. The method is based on advanced natural language processing techniques, aiming to identify the most relevant and crucial information in the analyzed texts. The method was evaluated using a dataset of texts containing port news. The results revealed the method's ability to generate accurate and concise summaries, highlighting its effectiveness in extracting crucial information. Additionally, the model demonstrated the ability to identify discrepancies and inaccuracies in the texts, suggesting potential utility in news verification systems.
The practical application of this prototype promises to significantly enhance efficiency in the analysis and understanding of texts related to the port sector, providing more condensed and relevant information. Its ability to detect inaccuracies also underscores its usefulness in promoting the accuracy and reliability of conveyed information, contributing to the integrity of news verification systems.
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