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AI Metadata Extraction and Filtering from Scientific Research Articles

1 October 2024
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Publisher : CrossML Blog

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This article discusses AI techniques for extracting and filtering metadata from scientific articles, highlighting recent advancements in natural language processing and machine learning. It explains how these AI-powered methods can improve the accuracy and relevance of metadata extraction, enabling better organization and retrieval of scientific knowledge. The article also explores how AI technologies can be applied to various research fields, enhancing data accessibility and efficiency. By incorporating these techniques, organizations can streamline their metadata extraction processes and make more informed decisions based on accurate and relevant data.

Author(s) :

Ishita Kaur

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Key topics

Data Science for social impact

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Technology for Social Change and Organisational Efficiency

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