Construction of a Scientific Literature AI Data System for the Thematic Scenario: Technical Framework Research and Practice

Construction of a Scientific Literature AI Data System for the Thematic Scenario: Technical Framework Research and Practice

[Purpose/Significance] Artificial intelligence is empowering scientific research and has become a major driver of scientific discovery. High-quality data resources for thematic scenarios are the key to training high-performance AI models. Given the complexity of scientific and technological (S&a...

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Bibliographic Details
Main Author: Zhijun CHANG, Li QIAN, Yaoting WU, Yunpeng QU, Yue GONG, Zhixiong ZHANG
Format: Article
Language:zho
Published: Editorial Department of Journal of Library and Information Science in Agriculture 2024-09-01
Series:Nongye tushu qingbao xuebao
Subjects:
ai data system|multi-modal deconstruction|semantically annotated data|data governance tool chain|data feature quantization
Online Access:http://nytsqb.aiijournal.com/fileup/1002-1248/PDF/1736761649736-1583837308.pdf
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