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Implementation of Text Mining for Evaluating the Relevance Between News Headlines and Content on a Web-Based Platform

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This analysis shows text mining improves relevance assessment of news headlines and content, highlighting model performance differences.

IndoBERT achieved a training accuracy of 0.9048, demonstrating significant effectiveness in analysis.
The evaluation indicates superior performance of IndoBERT over LSTM in assessing news content relevance.
Data collection involved 52,242 articles from major Indonesian news portals, emphasizing the scale of the research.
The study utilized web scraping and deep learning for analyzing text similarity among news articles.

Purnawati et al. (2025) studied this question.

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