Presentation demonstrates AI search capabilities in academic repositories, highlighting implications for data access.
This presentation demonstrates practical implementation of AI-powered search in academic repositories, moving beyond the "put an AI in it" hype to examine real capabilities and limitations. Using public data from Project Gutenberg, I'll showcase how Large Language Models (LLMs) enable semantic search that surpasses traditional keyword matching and manual tagging by understanding thematic relationships between texts.
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S. J. Eardley (2026) studied this question.
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