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Journal of Scientific Information Research

Keywords

large language model, intelligent agent, scientific and technical intelligence, domain-specific large model, ontology synergy⁃tion, artificial intelligence, knowledge organization

Abstract

Professor Mao Taitian and colleagues argues elucidates the adaptation logic, practical pathways, and prerequisites of intelligent agents to empower the high-quality development of scientific information. Professor Bao Yulai and colleagues advocate that integrating the perceptual elasticity of domain-specific large models with the cognitive rigidity of ontology can establish a new paradigm for intelligence services in complex scenarios. The synergy between the two can not only expand the theoretical boundaries of information science and serve national strategies, but also advance intelligence services from assisted analysis to intelligent decision-making. Professor Wei Jianxiang and colleagues point out that generative artificial intelligence has triggered problems such as synthetic data anomie, difficulties in auditing information pollution, and elevated risks of intelligence leakage. By constructing a human AI collaboration model, relying on intelligence thinking for deviation correction, implementing full-process verification, and enhancing personnel's intelligence literacy, such measures can ensure the secure and controllable utilization of intelligence resources. Professor Wu Peng and colleagues propose that scientific information empowers the integration of technological innovation and industrial innovation, and that artificial intelligence reshapes intelligence research capabilities and thus can assist in tackling key technological bottlenecks and fostering industries. It is necessary to consolidate the digital-intelligent foundation, promote intelligent upgrading, and make forward-looking strategic arrangements. Professor Yu Chuanming reveals that artificial intelligence mirrors the essence of information science, driving knowledge organization through a three-stage evolution of alignment, integration, and augmentation, ultimately transforming knowledge organization into a fully connected disciplinary network characterized by value emergence.

First Page

1

Last Page

9

Submission Date

7-May-2026

Revision Date

26-May-2026

Acceptance Date

8-Jun-2026

Published Date

1-Jul-2026

Reference

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Digital Object Identifier (DOI)

10.19809/j.cnki.kjqbyj.2026.03.001

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