25 December 2025, Volume 45 Issue 06

    

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  Research on Intelligent Knowledge Services and Cross-Domain Knowledge Alignment Methods for Medical Decision Support

  Gu Dongxiao Guo Shumin Su Kaixiang Yang Xuejie Zhu Kaixuan Wang Xiaoyu

  Library & Information. 2025, 45(06): 1-10. DOI:10.11968/tsyqb.1003-6938.2025066

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  The deep integration of artificial intelligence and the medical field makes the integration of cross-domain medical knowledge the key to improving the level of intelligent diagnosis and treatment. However, the semantic differences and expression barriers between different medical systems limit the effective integration and collaborative application of knowledge. This paper first constructs a three-layer framework covering resource aggregation, knowledge integration and intelligent services to support the whole process of medical decision-making from data fusion to knowledge services. Aiming at the core problem of cross-domain knowledge semantic alignment, the paper proposes a deep alignment method that integrates general and domain pre-training models, attention mechanisms and contrastive learning, and realizes accurate modeling and efficient alignment of complex semantic associations between heterogeneous medical texts through multi-level semantic extraction, dynamic weight focusing and contrastive semantic space optimization, effectively improves the accuracy and robustness of cross-domain knowledge alignment, and provides a technical foundation and practical path for the development of an intelligent decision support system that can deeply integrate multiple medical knowledge.
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  Research on Human-Machine Collaborative Methods for Semantic Knowledge Discovery in Chinese Medicine within a Digital-Intelligent Environment

  Liu Xuanqi Chu Wei Wang Xiaoyu Sun Jiayue Wang Yufei Gu Dongxiao

  Library & Information. 2025, 45(06): 11-24. DOI:10.11968/tsyqb.1003-6938.2025067

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  The digital and intelligent transformation presents significant opportunities for the modernization and intelligent servicing of Traditional Chinese Medicine (TCM) knowledge. However, the inherent characteristics of the TCM knowledge system—such as ambiguous terminology, multi-source heterogeneity, and semantic complexity—pose considerable challenges to its structured organization and intelligent application. This paper constructs a human-in-the-loop TCM semantic knowledge organization and service framework based on a "model generation—human correction—feedback optimization" paradigm. By integrating the automated extraction capabilities of large language models with the manual verification mechanisms of domain experts, the framework achieves precise identification and dynamic optimization of entities and relationships within TCM literature. Using the prevention and treatment of gastric diseases in TCM as a case study, the framework's application potential is validated in areas such as assisting clinical diagnosis and treatment, enabling personalized medication recommendations, and supporting proactive health management. This work contributes to the systematic transformation of TCM knowledge, its intelligent service delivery, and its deeper integration with modern medicine.
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  Research on Dynamic Management and Intelligent Service System of Traditional Chinese Medicine Knowledge Based on 5P Medical Model#br#

  Zhong Jinhong Liu Jia Yang Xuejie Sun Jiayue Gu Dongxiao Wang Xiaoyu

  Library & Information. 2025, 45(06): 25-32. DOI:10.11968/tsyqb.1003-6938.2025068

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  The sustained penetration of digital technologies and intelligent applications is reshaping the modes of knowledge production and service provision in healthcare systems. Within this context, traditional Chinese medicine (TCM) is encountering a structural transformation imperative in the domains of chronic disease management and full-cycle health protection. This paper anchored in the predictive, preventive, personalized, participatory, and precision-oriented principles of the 5P medical model, takes the current landscape of TCM knowledge resource digitization and intelligent service development as its analytical entry point. It systematically examines the practical challenges confronting TCM in the dynamic organization and intelligent management of knowledge, and further elucidates the underlying formation mechanisms across technological conditions, knowledge structures, and service scenarios. On this basis, a 5P-oriented framework for the dynamic management and intelligent service of TCM knowledge is developed. By integrating multi-level knowledge aggregation, dynamic knowledge graph modeling, and human-machine collaborative feedback mechanisms, the framework enables the coordinated evolution of knowledge organization and service provision, offering a structured pathway to support the standardization and sustainable development of intelligent TCM services.
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  A Data-Intelligence Empowered Framework for Smart Traditional Chinese Medicine Information Services

  Ni Beibei Wang Xiaoyu Wang Ying Sun Jiayue

  Library & Information. 2025, 45(06): 33-42. DOI:10.11968/tsyqb.1003-6938.2025069

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  With the deep integration of artificial intelligence technology and the modern medical system, as well as interactive innovation, traditional medicine is accelerating its transition into a new phase of digitalization and intelligence. The article first defines the conceptual essence of intelligent Traditional Chinese Medicine (TCM) and conducts an  analysis of the implementation mechanisms of digital intelligence technologies in typical scenarios such as rational medication review, disease risk prediction, TCM diagnosis and treatment decision-making, TCM knowledge organization, and TCM quality control. It further distills five core characteristics of intelligent TCM information services (preventive, predictive, personalized, participatory, and precision). Subsequently, from the perspective of patient trust, the article employs the structural equation modeling method to reveal the impact mechanisms of these five characteristics of intelligent TCM services on patient satisfaction. Finally, a comprehensive framework for a domain-wide intelligent TCM information service system driven by digital intelligence is constructed from five dimensions: guiding philosophy, knowledge window, technology window, application window, and policy window.
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  Risk Patterns and Governance Approaches for Network Information Content in the Era of Generative AI

  Li Yang Liu Bozhen

  Library & Information. 2025, 45(06): 43-52. DOI:10.11968/tsyqb.1003-6938.2025070

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  In the era of generative AI, the underlying logic and application scenarios of network information content have undergone new transformations, spawning an entirely new human-machine hybrid information environment. Network information content risks are confronted with the dual challenges of "disorderly growth" and "unbounded deviation" of AI-Generated Content (AIGC). This paper constructs a novel risk framework for network information content under the influence of generative AI technology, integrating both informational and systemic dimensions, and further develops and analyzes an AIGC risk pyramid model. Addressing these evolving risk patterns, the paper proposes a risk governance pathway for network information content in the era of generative AI based on agile governance principles, covering three key levels—governance philosophy, governance subjects, and tools—providing references for the future development of network information content ecosystems.
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  Ethics First: the Construction of an Artificial Intelligence Ethical Framework Centered on Human Beings

  Wang Dan Xin Meiting Tong Shangyi Luo Zhuoran Lu Wei

  Library & Information. 2025, 45(06): 53-65. DOI:10.11968/tsyqb.1003-6938.2025071

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  Large language models represented by ChatGPT have promoted the formation of a new paradigm of artificial intelligence, while also arousing people's fears and concerns about artificial intelligence-centered information processing, and there is a growing outcry regarding ethical issues arising from artificial intelligence. Firstly, this paper systematically sorts out relevant literature on artificial intelligence ethics and conducts an integrated review of 115 officially released artificial intelligence guidelines worldwide, analyzing the connotation of artificial intelligence ethics. Secondly, through data mining, it analyzes the multiple stakeholders and their behaviors in artificial intelligence ethics, and defines the boundaries and framework elements of artificial intelligence ethics. Finally, combining theory and practice, it constructs a human-centered artificial intelligence ethical framework integrating design ethics and social ethics.
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  Research on Optimization of Data Element Market Policy in the National Data Element Comprehensive Pilot Zone

  Li Wen Tang Guoao

  Library & Information. 2025, 45(06): 66-78. DOI:10.11968/tsyqb.1003-6938.2025072

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  The National Data Element Comprehensive Pilot Zones are regional innovative pilot zones in China aimed at promoting the market-oriented allocation of data elements and achieving efficient circulation and value release of data resources. There is an urgent need to optimize provincial (and municipal) data element market policies to improve the overall institutional framework and drive high-quality digital economic growth. By introducing the Policy Synergy Index (PSI), this paper examines how provincial-level data element market policies within the National Data Element Comprehensive Pilot Zones implement and align with central government policies, and employs the Policy Modeling Consistency (PMC) index model to evaluate their strengths and weaknesses, thereby proposing optimization recommendations for these policies. The findings indicate that the policies exhibit broad synergy, comprehensive coverage, and ample deployment of policy instruments; however, they underperform in synergy intensity, policy efficacy, policy type diversity, and policy subject diversity. Optimization should therefore focus on deepening policy transformation, enhancing policy predictability, strengthening synergistic effects, avoiding policy homogenization, and perfecting the overall policy architecture.
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  Digital Transformation of Public Cultural Services: Logical Implications, Risk Identification, and Governance Pathways

  He Zhiqiang Li Shaohui

  Library & Information. 2025, 45(06): 79-90. DOI:10.11968/tsyqb.1003-6938.2025073

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  The digital-intelligent transformation of public cultural service governance is an imperative of our times and the essential path to achieving high-quality development in public cultural services through digital and intelligent technologies. Based on the "value-space-technology" triad of the digital-intelligent transformation of public cultural service governance, this paper constructs an analytical framework for its logical implications, risk type identification, and governance pathways. It clarifies that this transformation encompasses three-tiered logics: a value logic shifting from supply-demand separation to co-creation of value; a spatial logic reinforcing data spatial justice and integrated urban-rural spatial planning; and a technological logic advancing from digitization to digital-intelligence. It further identifies the risks existing in the digital-intelligent transformation of public cultural service governance in the new era, mainly manifesting as three types of risks: value risks such as ethical misconduct and algorithmic bias; spatial risks including regional spatial fractures and disorder in data space; and technological risks encompassing tool-driven alienation and system security challenges. To enhance the effectiveness of digital-intelligent governance in public cultural services, efforts should focus on: addressing value risks through data ethics reshaping and algorithmic bias correction; addressing spatial risks by strengthening regional spatial justice and building trustworthy data spaces; addressing technological risks via adaptation of digital-intelligent technology alienation and reinforcement of system resilience. These measures will promote the high-quality development of the digital-intelligent governance of public cultural services.
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  Librarians' Artificial Intelligence Anxiety: Manifestations, Mechanisms of Influence, and Coping Pathways

  Chen Jingyi Wu Xiurong Chen Xiaonan Feng Changyang

  Library & Information. 2025, 45(06): 91-103. DOI:10.11968/tsyqb.1003-6938.2025074

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  The accelerating application of artificial intelligence (AI) in libraries has aroused anxiety among librarians regarding AI technologies. To promote AI-enabled library development, it is necessary to understand the influencing factors of librarians' AI anxiety. This paper employed semi-structured interviews with 48 librarians from 30 libraries in China and applied grounded theory to code the data, extracting the dimensions of anxiety perception, characteristics of their manifestations, and key factors influencing the generation of anxiety. The study identifies eight dimensions of librarians' AI anxiety perception and reveals the influencing mechanisms of anxiety perception from three aspects: subjective evaluation, contextual factors, and personal characteristics. The study further discusses and analyzes the situational expression of AI anxiety, the absence of emotional governance mechanisms, and the crisis of professional identity, and proposes coping pathways to mitigate librarians' AI anxiety.
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  Research and Implications of AI Competency Requirements for American Librarians Based on LDA Topic Modeling

  Sun Lijuan

  Library & Information. 2025, 45(06): 104-112. DOI:10.11968/tsyqb.1003-6938.2025075

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  Based on 134 recently released AI-related job postings in the US library field, this paper employs the Latent Dirichlet Allocation (LDA) topic model to conduct a quantitative analysis of job responsibilities and qualification requirements. It systematically reveals the characteristics of AI competency demands for librarians, and accordingly constructs an AI competency framework for librarians, clarifying the organic interconnections among various competency elements. Additionally, the paper summarizes the characteristics and experiences of AI competency requirements for librarians in US libraries, and proposes recommendations for the development of AI competencies among Chinese librarians. These recommendations include focusing on the cultivation of technical competencies in the Chinese context, promoting the in-depth integration of job responsibilities with library service scenarios, and establishing a governance guarantee and capacity-building system tailored to library contexts. This research aims to provide decision-making support for the talent team construction of Chinese libraries in the process of intelligent transformation.
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  Research on Construction and Application of Domain Knowledge Graph Empowered by Large Language Models

  Xu Hao Kang Zhenyuan Zhang Yan Deng Sanhong Zou Chen

  Library & Information. 2025, 45(06): 113-129. DOI:10.11968/tsyqb.1003-6938.2025076

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  This paper integrates Large Language Models (LLMs) with deep learning to propose an LLMDL framework for the entire Domain Knowledge Graph (DKG) construction process. The framework includes: data preprocessing drawing on text classification principles; semi-automated domain ontology construction via LLMs; domain-adaptive optimization of the W2NER named entity recognition (NER) model with LLM-based data annotation and result verification; relation extraction considering inter-relation correlations; entity alignment through the integration of SBERT and LLMs; and construction of high-quality DKG with scenario-specific applications. Experimental results show that the proposed method effectively balances text value while controlling text length; improves the F1 score of named entity recognition by 2.24% compared with the original model; achieves a 22.07% F1 score improvement in relation extraction compared with traditional BERT models; and 84.85% of entities achieve standardized expressions in knowledge fusion.
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  Research on the Situation Perception and Systematic Construction of China's Digital Aging Policy Development

  Zhang Xin An Yifang

  Library & Information. 2025, 45(06): 130-141. DOI:10.11968/tsyqb.1003-6938.2025077

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  China's digital elderly friendly policies have gone through three stages of development: exploratory initiation (2015-2019), rapid growth (2020-2021), and stable deepening (2022 to present). Through text analysis of 51 digital aging policies issued by the central and ministerial departments in China, it can be perceived that the logic of China's digital aging policies has achieved iterative upgrades from basic guarantees to technological empowerment, and then to ecological construction. The allocation of policy tools presents the characteristics of "heavy supply, weak environment, and light demand", and the effectiveness of institutional incentives and market traction has not been fully released. The participating entities form a non-equilibrium collaborative network led by the government, and the collaborative linkage mechanism among multiple entities still needs to be improved. Entering the period of the 15th Five Year Plan, a systematic construction of digital elderly friendly policies can be carried out from four dimensions: top-level design of rule of law, balanced policy tools, ecological coordination of subjects, and long-term governance guarantee.