The rapid rise of generative artificial intelligence is propelling digital humanities (DH) toward a paradigm shift to AI-driven intelligent humanities (AI-DH). This study provides a systematic account of this transformation by examining its external morphological evolution, internal methodological innovations, and underlying cognitive reconstruction. In terms of research morphology, AI-DH is characterized by human-AI collaboration, integrated and generalized technological architectures, the activation of data intelligence, and the emergence of novel research forms. Cognitively,AI-DH embodies the dialectical unity of human and machine intelligence, the convergence of humanistic rationality and probabilistic inference, and the coexistence of deep exploration and broad generalization. Methodologically, AI-DH demonstrates a theoretical shift from tool-based assistance to intelligent partnership, from humanities-centered to humancentered inquiry orientation and a transition from linear workflows to open generative systems. These shifts give rise to four emerging paradigm patterns: generative humanities, dialogic humanities, simulated humanities, and extended humanities. Overall, AI-DH not only expands the boundaries and capabilities of traditional DH but also reshapes its epistemic foundations and practical pathways, offering a systematic framework for the intelligent evolution of humanities research in the era of generative AI.

This paper systematically analyzes the core challenges faced by artificial intelligence technologies, particularly large language models (LLMs), in museum applications. By examining the structural limitations inherent in LLMs, it further explores the practical difficulties encountered by museums when implementing AI. In response to these issues,systematic countermeasures and a tiered governance framework are proposed to provide methodological support for the controlled implementation of AI in the cultural heritage sector. The study demonstrates that through prudent planning and scientific governance, artificial intelligence can serve as an effective tool to enhance the core operational capabilities of museums, offering sustainable momentum for innovation in cultural heritage preservation, research, and public services.

从2016年到2025年，上海图书馆开放数据竞赛已连续举办十年。作为国内公共文化领域最早探索向社会开放人文数据的实践之一，竞赛从单一机构以家谱专题资源为起点，逐步拓展至多家机构共同参与、涵盖多类数据主题的开放数据生态。十年来，竞赛持续推动开放数据体系建设，形成了“政府指导、图书馆主导、社会协同、企业助力”的合作格局，以及集“竞赛、宣讲、培训、展览和分享会”“五位一体”的办赛模式。竞赛以文化与科技融合的力量，让图书馆的数据“活”起来，让数据真正成为社会的新质生力，推动图书馆的角色从知识的“仓储”转变为智慧的“孵化器”。

During the Republican era in China, libraries and museums maintained a close and intertwined relationship, shaped by both foreign influences and indigenous factors. This article adopts a historical research approach to trace the transnational trajectory of the concept of “library-museum integration”—originating in the United Kingdom, transplanted to Japan, and subsequently introduced to China, where it underwent localized transformation. Under the influence of various educational ideologies including auxiliary education, social education, vocational training, and new democratic cultural education—the concept of “library-museum integration” in China manifested in several distinctive forms, including dual-purpose institutions, parallel development, scholarly community, and interdisciplinary academic programs. The article argues that institutional inertia rooted in aristocratic traditions played a key role in shaping the British model of “library-museum integration”. In Japan, driven by industrial development, the concept was functionally restructured. In the Chinese context, educational factors proved decisive in the evolution of the concept of “library-museum integration” in modern China.

With the rapid advancement of information technology, the development of smart libraries has become a core task and strategic direction for the transformation and development of the global library field. This paper,grounded in the context of smart library development being elevated to a national strategy during the 14th Five-Year Plan period, delves into the shift in smart library evaluation paradigms—from performance evaluation focused on efficiency to effectiveness evaluation emphasizing tangible outcomes. It systematically reviews the development of public library evaluation in China and its role in driving technological adoption. It distinguishes between performance evaluation and effectiveness evaluation by examining their core concepts, theoretical foundations, and international practices. Furthermore, it constructs a comprehensive evaluation framework encompassing multiple dimensions:smart spaces, smart services, smart resources, smart management, and smart librarians. Drawing on representative domestic and international case studies, this paper analyzes the key technologies, practical achievements, and challenges currently facing smart library development. It aims to provide theoretical references and practical pathways for the scientific evaluation and sustainable development of future smart libraries, ultimately driving the professional advancement of library services through management empowerment. This will enable libraries to demonstrate their irreplaceable social value in the era of digital intelligence.

By conducting a systematic study of China’s artificial intelligence governance policies through thematic modeling and quantitative evaluation, this paper provides support and guidance for policy optimization. Effective data from the 92 nationallevel artificial intelligence governance policies issued in China from 2017 to the 15th of March, 2025 were preprocessed.The BERTopic model was used to identify policy themes, calculate keyword c-TF-IDF weights, and three other thematic indicators, and combined with policy content to conduct an in-depth analysis of governance policy priorities. Based on thematic modeling, the PMC policy evaluation model was constructed to conduct empirical quantitative analysis on nine representative policy documents. The BERTopic model identified 13 themes, covering nine key areas of China’s AI governance policies. The PMC index model indicates that the overall policy level is good, but further optimization is needed in terms of governance framework, governance tools, and governance entities. Based on this, policy recommendations were proposed, including the construction of a classified governance policy framework, the combination of policy tools, and the promotion of collaborative governance, to serve China’s AI governance practices.

With the rapid advancement and widespread application of artificial intelligence (AI) technology, libraries-an essential institution for knowledge preservation and public service-are encountering unprecedented opportunities and profound challenges. AI holds the potential to significantly enhance operational efficiency and deliver more personalized,intelligent services to users. However, issues such as industry transformation, practical difficulties in technology implementation, and the adaptation of librarians’ skills have also emerged as pressing concerns for the library sector.This paper draws on the core discussions from the Directors’ Forum at the 21st Advanced Digital Library Seminar (ADLS 2025) and integrates insights from the industry and the academic to systematically explore new development pathways and strategies for libraries in the AI era, covering dimensions such as resource development, service models, spatial design, and professional competencies. The study aims to provide theoretical references and practical guidance for libraries undergoing transformation in this new era, ensuring their sustainable development and value redefinition amid the AI wave while maintaining their critical role in an intelligent information environment.

Artificial intelligence (AI) is reshaping scientific research paradigms at an unprecedented speed and breadth.From protein structure prediction to assisting drug development, AI technology has become an important tool in scientific research activities. However, current AI still has significant limitations in reasoning ability, knowledge generation, and experimental design, and cannot fully replace the role of human scientists. As a part of the knowledge infrastructure, the library must reposition its function and value in the scientific research ecosystem. Based on the current development trend of AI scientific applications, this article analyzes its impact and challenges on libraries, and proposes five key action strategies for the future to achieve the transformation from an “information service provider” to a “research collaborator”.

Addressing the static limitations in the study of the evolution of Chinese painting theory, this research employs digital humanities technologies to analyze the patterns of conceptual evolution and the mechanisms of artistic innovation.Based on over 1 400 pieces of painting theory literature from the pre-Qin period to the Ming and Qing dynasties, a four-dimensional evaluation system was constructed using text mining methods to identify frequent terms. The TF-IDF algorithm was used to detect hot terms, and a hotspot index was established based on term weights. Through diachronic novelty and intergenerational inheritance analysis, new terms were identified, and a vitality index was created based on the mean weight of new terms. The study found that 23 high-frequency core categories, such as “brush” “ink” “mountain” and “water” form a cluster of (trans-temporal) concepts. Their evolution exhibits three distinct stages: the pre-Tang system of form and spirit realism, the Song-Yuan shift towards expressive abstraction, and the Ming-Qing period of stylistic rigidity. Artistic innovation follows a “double-peak decay” pattern, with the Song dynasty marking the peak of theoretical development,while the Ming and Qing dynasties fell into a vitality crisis due to technical summarization. This research provides a quantitative paradigm for analyzing traditional art theories.

In studies on migration and remittances, the impact of kinship strength on international remittances lacks empirical testing. This paper constructs a remittance database of Chaozhou-Shantou immigrants in Southeast Asia from 1915 to 2000 based on the Chaozhou-Shantou Overseas Correspondence archives. Within the framework of digital humanities, it reconstructs kinship structures based on the titles used in the correspondence, quantifies transnational kinship indices, and, combined with clan associations, hometown associations, Chinese-language newspapers, and genealogical records, constructs social network indicators. Ordinary least squares and two-way fixed effects estimates show that the recipient’s kinship intensity index is the most robust predictor of remittance behavior: each increase in kinship rank is associated with an increase of about 20% in remittance frequency relative to the sample mean. Once sending and receiving locations are held constant, the explanatory power of associational and media networks declines, and Qiaopi agencies function mainly as transaction channels rather than sources of motivation. Interaction terms indicate that genealogical documentation amplifies the effect of kinship,suggesting that lineage institutions strengthen family-based remittance obligations through collective memory and reputational constraint. The study integrates historical textual sources with econometric methods and provides Chinabased evidence on remittances from a social network perspective.

In the context of national strategies for educational empowerment and digital China initiatives, the development of smart libraries has become a pivotal component of the national cultural digitalization strategy, necessitating artificial intelligence (AI) to drive service model innovation. This paper focuses on university library circulation and reference service scenarios, guided by the practical needs of faculty and student users. A general-purpose agent-based intelligent question-answering system was developed using a knowledge base of frequently asked questions (FAQs) in circulation operations. By integrating AI large language model to achieve automated knowledge reasoning and response generation, the system significantly enhances service efficiency while optimizing limited human resources. Empirical results demonstrate that this solution markedly improves library service effectiveness, provides a reusable technical framework for intelligent transformation in other domains, and contributes to advancing digital transformation and modernization in higher education.

The proliferation of Artificial Intelligence Generated Content (AIGC) is fundamentally challenging the ontological foundations and managerial logic of Information Resource Management (IRM). Traditional IRM paradigms, predicated on a static lifecycle, prove inadequate for the extreme dynamism, emergent collaboration, and heterogeneous complexity of the AI open-source ecosystem. This paper, through an analysis of communities like Hugging Face and domestic models such as DeepSeek and Qwen, identifies three critical dimensions of generative information resources: Throughput (T),Quality (Q), and Capability Ceiling (C). Integrating insights from established theories, this paper constructs the dynamic Information Resource Management Theory (IRMT), a novel framework featuring the T-Q-C trade-off triangle to guide the strategic optimization of AI resources. This work offers more than a new theoretical paradigm for an autonomous IRM knowledge system in the AIGC era; it also delineates a practical path toward achieving efficient application of domestic AI and technological self-reliance, especially under computational constraints. Future research avenues include the quantitative modeling of the T-Q-C framework, the integration of ethical governance, and the extension of the theory to multimodal and agent-based systems.

The wave of large language model technologies has fostered the widespread development of generative AI (GenAI) tools and the upgrading of the knowledge service paradigm. Various organizations have chosen different upgrade paths in the face of the new window of knowledge services brought by GenAI tools. This paper analyzes the four major application directions and differentiated application trends of GenAI tools in the field of knowledge service through case studies, and points out that literature data platforms need to pay more attention to the application of GenAI tools in intelligent knowledge retrieval. Taking the construction of the AI assistant to modern literature research of “Quan Guo Bao Kan Suo Yin” as an example, the article provides a reference for the intelligent transformation of other literature database by deconstructing the upgrading paths and practical effects.

This study tackles the issues of lack of narrative appeal, low engagement and poor historical authenticity in digitizing red culture resources, by proposing an interdisciplinary framework for red-themed educational games, integrating self-determination theory and flow theory to address adolescent psychological needs. The approach employs retrievalaugmented generation (RAG) and a dual-layer prompt mechanism to dynamically retrieve knowledge and ensure content accuracy, ensuring historical authenticity, and effectively enhancing the interest and immersive experience of red education.A game prototype, Retracing the Red Journey, was developed using data from the Shanghai Library and Jiaxing Library.Results confirm its effectiveness in enhancing user immersion, engagement, and historical understanding, offering a practical model for innovating red culture education.

Against the backdrop of the rapid iterative development of artificial intelligence, what obvious changes will occur in an organization's knowledge management is a theoretical and practical issue worthy of study. Based on the classic SECI process model of knowledge management and Don Ihde’s human-technology relationship theory, this article explores the development trend of organizational knowledge management under artificial intelligence from multiple dimensions. The substitutability of the artificial intelligence knowledge engine will lead to the development and changes of the knowledge private domain, and organizations will pay more attention to the construction of the knowledge private domain and give rise to the path of the new apprenticeship system. The development trend of this knowledge private domain and the new apprenticeship system is expected to provide valuable inspirations for organizations to balance knowledge security and innovative vitality, and promote the in-depth study of knowledge management theory and the transformation of practice.

The Information Processing System for Chinese Characters (also known as “Project 748”) is a national key scientific and technological research project initiated by China. “Project 748” aims to change the backward situation of China’s print industry and solve the problem of computer information processing for Chinese Characters. “Project 748” has promoted the all-round development of information processing technology for Chinese Characters, and also promoted the informatization progresses of library and information cause, which is a milestone in the development history of library and information technology in China. With historical research method and network survey method, this paper systematically reviews the development history of “Project 748” and one sub project “Intelligence Search Using Chinese Characters”, analyzes its important significance in the history of library and information technology in China, and provides references for the research and development of library and information technology in China.

This article analyzes the reader recommendation and purchase service model and its development, and proposes a reader recommendation and purchase architecture based on a closed-loop service chain of “demand capture-human-machine processing-feedback incentives-optimization upgrade” to address the challenges of reader participation, process management,and technological ecology in traditional recommendation and purchase models. The study not only elaborates on the process design and functional characteristics of the architecture in detail, but also constructs a smart transformation path for recommendation and purchase service based on artificial intelligence technology, hoping to provide reference for the path and ecological reconstruction of traditional recommendation and purchase services, thereby further improving the service quality of library reader recommendation and purchase service and continuously releasing its effectiveness in the transformation of library services.

The new wave of artificial intelligence (AI) technology is profoundly propelling human society towards comprehensive transformation, and a new era of AI-driven scientific research (AI for Science) is on the horizon. The paradigm of scientific research is undergoing an unprecedented acceleration in transition. This article analyzes the concept and research significance of AI for Science, reviews the development status of AI for Science from basic disciplines such as life sciences, materials sciences, physics, mathematics, chemistry, and earth sciences, discusses the transformative role of artificial intelligence in scientific research, and explores its guiding significance for future research directions. It also discusses the challenges faced in areas such as scientific research data, ethical safety, computational resources, and talent cultivation, in order to provide strategic insights and response strategies for the future development of the scientific research field.

In the context of rapid information technological advancement, the museum industry is undergoing profound transformation. The integration of digital technologies, particularly artificial intelligence, has not only reshaped the presentation of exhibits but also revolutionized visitor interaction experiences. Placing visitors at the center has always been a cornerstone of museum service philosophy. The development of smart guided tour systems, as a best practice of the convergence of technology and humanistic values, is leading new directions in museum education, communication,and service experiences. This paper clarifies the current state of museum guided services, the design of guided functions, and their application value. It further analyzes the challenges and proposes optimization strategies for the construction of smart guided tour systems in museums, aiming to provide insights and strategies for the sustainable development of museums.

To understand the formation of academic figures’ relationships in the Song Dynasty and explore the integration path between digital humanities technology and traditional historical research, a Song Dynasty academic network involving 1 987 scholars and 2 742 groups of relationships was constructed based on the china biographical database(CBDB). The research focused on three core issues: the impact of scholars’ attributes (hometown, school identity,etc.) , social capital (centrality, structural holes, etc.) , and the endogenous structure of the network (reciprocity,transitivity, etc.) on the establishment of academic relationships. Geographic proximity and homogeneity of school identity have a significant positive effect on the formation of academic connections. The network shows strong reciprocity but suppressed transitivity, reflecting the bidirectionality of academic interactions and the competitive exclusion between schools. In terms of social capital, centrality, especially degree centrality and eigenvector centrality,has a significant impact on relationship building, while the role of structural holes is limited. This study provides empirical evidence for understanding the social foundation of academic dissemination in the Song Dynasty and offers a new path for the integration of digital humanities and traditional historiography.

Taking the foreign-language red literature collection of the Renmin University of China Libraries as the research object, this study defines the concept of “foreign-language red literature”, reviews the current status of the collection,summarizes the workflow, elaborates on the research path, and analyzes the issues discovered and proposes solutions.Finally, it provides prospects for strengthening the organization, research, and utilization of foreign-language red literature in university libraries from aspects such as protection and restoration, development and utilization, and talent cultivation.

This paper focuses on the construction of a knowledge graph for the chronological resources of Xian Xinghai.Based on Qin Qiming’ Brief Chronicle of Xian Xinghai (1905—1945), an ontological knowledge model was developed,encompassing core entities such as persons, time, locations, events, works, and documentary sources. The Neo4j graph database was employed for data storage and relational querying, while the Vis.js library facilitated the dynamic visualization of Xian Xinghai’s social network and life trajectory. The results demonstrated that knowledge graph technology can effectively enhance the analyzability and visualization of Xian Xinghai’s life events, social networks, and artistic creation context, overcoming the limitations of traditional linear chronological representations and providing new research methods and pathways for understanding his music and revolutionary practices across different regions and stages. Future work may focus on enhancing the efficiency of knowledge extraction, expand data sources and enhance the interactive visualization experience.

As an innovative catalyst driving the integration of technology and culture, metaverse technology has pioneered new pathways for the digital transformation of the museum industry. This study takes the Shanghai Astronomy Museum as its research subject, systematically exploring the innovative applications of metaverse technology in museum management and services. By establishing a digital twin platform, the Shanghai Astronomy Museum has achieved intelligent management of venue operations, significantly enhancing operational and maintenance efficiency as well as emergency response capabilities.Through the development of the "Walking Planetarium" XR project, immersive experiences have been effectively realized,expanding the provision of high-quality science education resources. This research offers practical references for promoting the application of metaverse technology in cultural venues and provides insights for the digital transformation of museums and cultural institutions.

Transformative agreements play an important role in advancing open access and open science. Compared with foreign countries, mainland universities in China have insufficient understanding of open access transformation, and carry out relatively few practices about it. This paper first analyzes the current situation of global open access transformation practice, then takes the United Kingdom, Germany and Netherlands as examples to analyze the effectiveness of transformative agreements from the dimensions of promoting open access publishing, controlling publishing costs, and improving the impact of academic achievements. Finally, this paper takes the University of Electronic Science and Technology of China as an example, and selects Cambridge University Press, RSC Press and ACM Press as representatives, which have their own characteristics on open access transformation schemes, to elaborate the specific process and precautions for individual institutions to evaluate the feasibility of implementing open access transformation. Exploring diversified transformative agreements, issuing support policies for open access publishing, providing sufficient financial guarantees, and increasing the publicity and promotion of open access publishing and open access transformation can provide strong support for the implementation of open access transformation in China.

This study focuses on the activities and practices of Lu Xun during his Shanghai residence period (1927—1936)as the primary research object, with the aim of systematically revealing his behavioral strategies and intellectual trajectory within a specific historical context through digital methods. First, by integrating linked data and narrative theory, a digital storytelling model was constructed to support semantic associations and spatiotemporal visualization. Second, resources such as the Shanghai Library API and Lu Xun’s chronology were systematically integrated and organized, on which basis a digital storytelling platform was developed to realize the narrative presentation of Lu Xun's life trajectory and Shanghai’s urban space in spatiotemporal dimensions, followed by an analysis thereof. This study achieves visualized narratives based on spatiotemporal semantics, provides a verifiable digital storytelling paradigm for research on Lu Xun’s later thoughts, and expands the methods of digital humanities in the narrative analysis of historical literature.

Archives have emerged in the open science movement. The two-way interaction between open science movement and archival information services lays the scientific foundation and necessity for exploring archival information services for open science. This paper takes the four pillars mentioned in UNESCO Recommendation on Open Science,including open scientific knowledge, open scientific infrastructure, open participation, and open dialog, as a research framework, connects their conceptual connotations with the archival information service scenarios, and explores the direction of the development of archival information services in the context of open science. There are four practical scenarios for archival information services for open science: open archival knowledge service scenarios, open archival infrastructure, open public participation scenarios, and open dialogue scenarios. Providing archival information services for open science requires archives to improve the openness and sharing of archival resources, strengthen the functional construction of open archival infrastructure, build an open and participatory archival practice ecosystem, and pay attention to integrating the concept of collaboration into archival services. In the future, archives in China should adhere to the principle of dialectics and explore new development paths for archival information services in the open science movement.

This study targets the national security intelligence analysis scenario, aiming to overcome the informational limitations of single-modal data analysis and enhance situational awareness in complex scenarios. Based on deep learning theory, this paper constructs a heterogeneous data representation model from the macro perspective of multimodal data fusion, organizes a cross-modal data fusion framework, and introduces a dynamic weight allocation mechanism to achieve effective integration of multi-source heterogeneous data such as social media text, video, audio, satellite imagery, and network traffic. The research indicates that, in a complex data ecosystem, attention should be paid not only to the granularity of multimodal data fusion in open-source intelligence, but also to the requirements of intelligence tasks, enabling rapid and accurate fusion to form a practical and feasible industrialized process.

In the “screen-reading era”, user demand for knowledge content in media formats such as video, audio, and images has surged dramatically. During the 15th Five-Year Plan period, libraries are undergoing a critical transition from intelligent to smart operations. Within the macro framework of building high-quality data resources, establishing a comprehensive media knowledge organization system, efficiently managing media resources, and unlocking their new value to provide users with diverse knowledge access and service support has become particularly crucial. This paper examines the case study of Guangzhou Library’s smart media resource management and service platform development. Addressing current challenges in library media resource management and application, it summarizes experiences and outcomes in resolving these pain points, and proposes further concepts for the 15th Five-Year Plan period. Further envisions how to deepen and refine media asset intelligent applications from three dimensions—“enhancing resource utilization, enhance AI capabilities, and building a humanistic hub”—to unlock the platform’s potential value in public cultural services and academic research support. This aims to provide new pathways for consideration in the construction and application of high-quality data resources for libraries.

With the rapid development of general artificial intelligence large model technology, humanoid robots, as a cutting-edge achievement integrating artificial intelligence and physical robotics, have attracted widespread attention.Focusing on the theme of library humanoid robots, this paper systematically reviews and analyzes their current development status and existing bottlenecks through methods including web-based survey, literature analysis, and content analysis, from multiple dimensions including academic literature, major products, and application practices. Meanwhile, by tracking the latest technological advancements and development trends, it proposes outlooks on future innovation paths and implementation strategies for library humanoid robots, aiming to provide references for the theoretical and practical development of smart libraries.

The deepening development of digitization and intelligence has generated a huge demand for digital intelligent talents. In the array of disciplines and majors in universities that cultivate digital intelligent talents, the major of information management and information system occupies an important position. This study contributes to the theoretical development of the academic discourse on cultivating digital intelligent talents in the field of information management and information system and responds to the needs and challenges posed by the era of digital intelligence at a practical level. Based on the definition of the competency of digital intelligence talents for the major of information management and information system, we collect data on digital intelligence-related job postings for undergraduates in information management and information system from a large online job search website. It then extracts relevant categories using grounded coding method, ultimately developing a demand-driven competency model of digital intelligence talents for the major of information management and information system. The model identifies 13 main categories, classified into three groups: knowledge, skills, and personal qualities, with intrinsic logical relationships among them. The model shows that digital intelligence has reconfigured the traditional core competencies of talents in information management and information system, further expanding the competency structure of talents in the context of big data, giving more prominence to development skills,and encompassing a broader range of new skills.

In the age of artificial intelligence, how to meet users’needs for information retrieval becomes a new challenge and information service platform for libraries. Retrieval-Augmented Generation (RAG) effectively solves the hallucination of large language models, which improves the accuracy and user satisfaction of intelligent retrieval applications based on large language models. On the basis of RAG models, this article has studied and constructed an intelligent retrieval system leveraging the digital resources of Quan Guo Bao Kan Suo Yin (CNBKSY). By establishing a private literature knowledge base with high-quality digital resources, and utilizing the powerful ability of large language models to understand and generate natural language, this system improves accuracy rate by integrating retrieval strategies such as query rewriting, multi-route retrieval and reranking in the form of collaboration between large language models and small neural network models.Furthermore, it has achieved the transformation of library collections from digitization to intellectualization, which further enhances the service quality of CNBKSY.

In the context of the marketisation of data elements, revealing the integration mechanism between scientific data and the various elements of new quality productive forces can provide theoretical references and practical guidance for promoting the value transformation of scientific data and accelerating the development of new quality productive forces. Following the “path dimension-implementation path” framework, this paper analyses the path dimension of scientific data empowering the formation of new quality productive Forces from three horizontal dimensions: technology,institutions, and ecology. It then proposed specific implementation paths for scientific data to empower new quality productive forces from three vertical dimensions: new-type workers, new-type means of production, and new-type objects of labour. Scientific data empowers the formation of new quality productive forces through three pathways: driving innovation in research paradigms, facilitating the market-based allocation of data elements, and constructing cross-subject collaborative innovation networks. This can be achieved by enhancing the data literacy of new-quality workers, implementing legal governance of scientific data, and endowing traditional labour objects with new characteristics to empower new-quality workers, new-quality labour materials, and new-quality labour objects through scientific data.

This study takes the “Vessel of Knowledge” poster as an entry point to explore the innovative applications of AIGC (Artificial Intelligence Generated Content) technology in library reading promotion design. The article examines the selection and application of AIGC tools during the creation process of the “Vessel of Knowledge” poster, including theme interpretation, determining symbolic design methods, exploring and filtering visual elements, analyzing tool characteristics, prompt engineering, and optimizing details. It analyzes the effectiveness of AIGC in areas such as creative generation, visual presentation, and efficiency improvement. Based on this case, the article further explores how AIGC technology can expand from single-media design to diverse scenarios in library reading promotion. Meanwhile, it also points out the limitations of AIGC technology, such as randomness and uncontrollability of content, limited emotional and cultural expression, copyright risks, and challenges in personnel adaptability. Therefore, the study proposes strategies for libraries, including cultivating internal talent, enhancing reader interaction, integrating cultural resources and services,and fostering multi-party collaboration. In the future, the application of AIGC technology is expected to develop toward intelligence, immersion, and cross-disciplinary collaboration, potentially injecting new vitality into library reading promotion and enhancing cultural communication abilities.

This paper proposes a concept for systematically managing museum data using artificial intelligence technology based on attention mechanisms and explores the technical implementation methods. Specifically, it involves integrating all museum data into a unified data warehouse and employing large language models to interpret requests expressed in natural language, translating them into programming languages capable of processing multimodal data such as images, text, and audio. These languages are then used to perform tasks such as statistical analysis, querying, summarization, and reasoning.Through the collaboration of the data layer, processing layer, and interaction layer, the system not only ensures the accuracy,completeness, and comprehensiveness of the extracted data but also derives information from data analysis, integrates information into knowledge, and ultimately develops intelligent capabilities.Additionally, it addresses the long-standing issue of data silos within various museum business systems.

As the core carrier of the public cultural service system, public libraries face the dual challenges of precise service provision and scientific feedback mechanism under the development concept of user demand-oriented. Aiming at the current practical problems such as the single dimension of user demand identification and insufficient utilization of feedback data,this research innovatively constructs a hybrid analysis framework that integrates Bert pre-training model and LDA topic model. The Python web crawler system was used to obtain the corpus of user comments on the local internet living platform,and Bert was applied for fine-grained sentiment analysis to quantitatively analyze the spatial distribution characteristics and regional differences of user satisfaction. On this basis, a double-channel LDA topic analysis framework of affective stratification is introduced to systematically deconstruct the characteristics of user demends and emotional motivations from 31 484 valid comments. The empirical study shows that: (1) users generally hold a positive attitude towards library services, which has a slightly higher indication in the east, Hong Kong, Macao, Taiwan and central regions, and a slightly lower indication in the west and northeast regions; (2) the positive evaluation focuses on the dimensions of infrastructure intelligence, cultural resource richness and digital service innovation; (3) negative opinions mainly focus on the rationality of spatial planning and the timeliness of service response. Based on this, this paper proposes a targeted optimization path, aiming to provide data support for the improvement of user feedback mechanism and intelligent transformation of public libraries under the background of digital intelligence, and promote the sustainable optimization of public cultural institutions’ services.

In August 1974, Chinese government launched a key project – "Information Processing System for Chinese Characters (also known as "Project 748"). "Project 748 " aims to change the backward situation of China's print industry and solve the problem of computer information processing for Chinese characters. " Project 748" has promoted the all-round development of information processing technology for Chinese Characters, and also promoted the informatization progresses of library and information cause, which is a milestone in the development history of library and information technology in China. With historical research method and network survey method, this paper systematically reviews the development history of " Project 748" and one sub project " Intelligence Search Using Chinese Characters ", analyzes its important significance in the history of library and information technology in China, and provides references for the research and development of library and information technology in China.

In recent years, China’s open access (OA) has seen a booming development, and its participation and contribution in the international OA field is increasing. This paper systematically combs through the progress and effectiveness of China’s OA practice, deeply analyzes the shortcomings and problems faced, and puts forward corresponding suggestions and countermeasures for the existing problems, with a view to providing reference for the development of China’s OA practice.The study concludes that, in the face of the current problems of insufficient number of high-quality OA journals, unbalanced publishing structure, incomplete coverage of disciplines, not yet in line with the mainstream OA model, and the service level to be improved, it is proposed that China needs to further improve the policies and supporting services, promote the longterm preservation of OA resources, optimize the transformation of OA journals’ publishing, pay attention to the new model of S2O, integrate the resources of knowledge bases, and enhance the role of library and information institutions in OA services,as well as to be alert to intellectual property risks in the open access model.

Recently, DeepSeek has emerged as a phenomenal product due to its high efficiency, open-source nature, and low-cost training, fueling a nationwide AI boom. This interview explores the profound impact of the large AI model DeepSeek on the library industry. During the discussion, Mr. Liu Wei elaborated on DeepSeek’s technical advantages and analyzed its potential in library services such as knowledge provision, reference consultations, and intelligent agent applications. Mr. Liu emphasized that libraries must transform to adapt to the AI era, suggesting measures such as deploying local models, developing intelligent agents, and training readers to enhance library services. Furthermore, he pointed out that as technological and knowledge gaps continue to widen, librarians should actively embrace the changes of the times and technological advancements while steadfastly upholding their role as knowledge intermediaries.

As a high-quality domestic open-source large language model, DeepSeek will accelerate the application of generative artificial intelligence technology across various industries. University libraries stand at a pivotal transformation period in the AI era. The Yunhan Community invited multiple experts from university libraries to introduce the current status of AI applications in university libraries, focusing on DeepSeek’s deployment, application scenarios, knowledge base construction, and AI literacy education. The study discussed the challenges that university libraries face when advancing AI services in terms of computational resources and data accessibility, integration between the technological and operational,role transformation directions, and academic ethical standards. The research proposes achieving resource sharing through alliances, building academic knowledge bases oriented toward open science, constructing multi-level AI literacy education systems, and reconstructing knowledge service models based on large language models, thereby promoting paradigm transformation in library services in the AI era and achieving high-quality development.

This paper proposes a concept for systematically managing museum data using artificial intelligence technology based on attention mechanisms and explores the technical implementation methods. Specifically, it involves integrating all museum data into a unified data warehouse and employing large language models to interpret requests expressed in natural language, translating them into programming languages capable of processing multimodal data such as images, text, and audio. These languages are then used to perform tasks such as statistical analysis, querying, summarization, and reasoning. Through the collaboration of the data layer, processing layer, and interaction layer, the system not only ensures the accuracy, completeness, and comprehensiveness of the extracted data but also derives information from data analysis, integrates information into knowledge, and ultimately develops intelligent capabilities. Additionally, it addresses the long-standing issue of data silos within various museum business systems.