The Regulationon on Promoting Nationwide Reading officially came into effect on February 1,  2026,  marking a new era of legal protection for nationwide reading initiatives. Xu Yan points out that the secondhand book industry is an important carrier of cultural heritage and knowledge dissemination. In response to the shortage of quality secondhand book sources,  Xu calls on libraries to remove excessive duplicate copies,  different editions,  and books with zero circulation from their collections so that these books can re-enter the circulation market. This would optimize resource allocation,  support the development of the secondhand book industry,  and promote nationwide reading,  thereby forming a virtuous cycle. Li Donglai notes that libraries should seize this opportunity to assume the role of the “core force,  main platform,  and key organizer” of nationwide reading. Addressing issues such as insufficient funding in some county and district libraries and the lack of grassroots reading facilities,  Li calls on libraries to make effective use of legal frameworks,  actively act as advocates for citizens‘ reading rights,  and strengthen their own institutional capacity. This would help extend reading promotion to grassroots communities and deepen its impact,  enabling libraries to achieve transformative development within the process of rule-of-law advancement. Xu Qiang interprets the core principles of the Regulation on Promoting Nationwide Reading and outlines how they connect with the Public Cultural Service Guarantee Law of the People’s Republic of China and the Public Library Law of the People‘s Republic of China. Using Shanghai as a case study,  Xu analyzes the statutory positioning and service innovations of public libraries in promoting nationwide reading. Shanghai has developed a structure characterized by “a leading central library,  coordinated branch libraries,  and full coverage via grassroots service points”,  though challenges such as uneven resource distribution remain. Future efforts should focus on improving the legal framework and deepening practical implementation,  while strengthening digital transformation and full life-cycle services. Zhang Yan points out that,  compared with the Public Cultural Service Guarantee Law of the People's Republic of China and the Public Library Law of the People's Republic of China,  the Regulation on Promoting Nationwide Reading demonstrates significant differences and distinctive highlights. By establishing rigid coordination mechanisms and accountability clauses,  the regulation shift nationwide reading governance from “soft advocacy” to “hard constraints”, significantly strengthening the network and collaborative influence of libraries in reading promotion. Jin Keke explores the central role of libraries in promoting nationwide reading and possible pathways for local legislation. From three perspectives,  namely,  spatial infrastructure,  activity organization,  and reading surveys,  Jin demonstrates the unique functions of libraries. Compared with the  Public Library Law of the People's Republic of China,  the Regulation on Promoting Nationwide Reading further strengthens the responsibilities of public libraries in areas such as reading guidance,  facility upgrades,  and safety assurance,  while also offering recommendations for local legislative development.

This paper analyzes the core journal papers and dissertations in China that employ grounded theory as a research method. Based on this review,  the study reflects on and summarizes the key problems existing in the current application of grounded theory within Chinese Library and Information Science (LIS) research. It suggests that the grounded theory is not only a research methodology,  but also a form of research logic. The conclusion derived from grounded theory studies should essentially be regarded as a theoretical hypothesis that require further verification. The paper also discusses how to ensure the accuracy of coding in grounded theory and how to achieve theoretical saturation. By clarifying conceptual understandings and methodological principles,  the study aims to promote the innovative development of grounded theory application in the LIS research. Grounded theory research is suitable for research topics that require long-term commitment and effort.

The world today is undergoing profound changes unseen in a century,  reshaping the global political and economic landscape. Think tanks play a pivotal role in fostering intellectual innovation and shaping policy decisions,  establishing themselves as key actors in global governance. Against the backdrop of evolving global think tank trends and best practices,  understanding how these institutions maintain resilience and influence in an increasingly complex and uncertain world is critical for advancing the high-quality development of new-type think tanks with Chinese characteristics. This study analyzes The On Think Tank State  of the Sector Report 2024 released by the On Think Tanks (OTT) platform,  offering a systematic examination of the current landscape,  emerging trends,  and key challenges facing the global think tank sector. It explores how think tanks address critical issues,  such as funding shortages,  talent attrition,  and political polarization,  through institutional innovation and organizational transformation. For Chinese think tanks,  leveraging global experiences is essential to strengthening institutional foundations,  broadening international perspectives,  accelerating digital and intelligent transformation,  and actively participating in global governance to enhance their resilience and amplify their impact.

To implement the Third Plenary Session of the 20th CPC Central Committee's directive on “establishing mechanisms for channeling quality cultural resources directly to the community level, ” more robust data reflecting community-level public cultural conditionsare required. This study utilizes interviews and fieldwork to examine the operational challenges in community statistical surveys and the institutional factors underlying these challenges within the “practice-institution” framework based on the operation of the public cultural service system. The research demonstrates that the market-oriented circulation of data as a production factor presents viable opportunities to address these challenges. By establishing three guiding principles for introducing external data sources and developing a five-pathway data supplementation framework,  this study proposes a systematic,  cost-effective approach to integrate fragmented societal data. These methodological innovations enable more accurate representation of community-level cultural conditions and provide a data-driven basis for scientific decision-making in community public cultural services.

Libraries play an important role in promoting the achievement of global sustainable development goals (SDGs). However,  systematic and theoretical research on global library sustainable development practices remains insufficient. This study applies thematic analysis to encode three levels of themes from 61 SDG stories reported on the IFLA Library Map of the World platform. Through processes of conceptualization,  naming,  abstraction,  and integration of the corpus, the study identifies 69 initial categories,  23 main categories and 4 core categories related to library practices that promote sustainable development. It explores practical pathways through which libraries contribute to the achievement of the SDGs. The results suggest that a framework for sustainable development practices in libraries has taken shape,  characterized by an SDG-oriented approach,  a user-centered focus,  multi-stakeholder collaboration,  and innovative service initiatives as key drivers. The library's actions in promoting sustainable development also demonstrate their distinct characteristics. In the future,  libraries need to further clarify their role in sustainable development practices,  strengthen the leading role of library associations and professional organizations,  and enhance the broader social influence of their practical initiatives.

Based on a systematic review of the evolution and limitations of bibliographic systems, this paper proposes a next-generation catalog architecture for the era of generative artificial intelligence—Generative Public Access Catalog(GPAC). Centered on the core logic of “Integration-Understanding-Generation-Service,” GPAC integrates large language models, semantic retrieval, knowledge graphs, intelligent metadata, and verifiable generation mechanisms to create a new paradigm of intelligent catalog system based on natural language interaction, semantic intent parsing, and knowledge generation. Importantly, OPAC has not been replaced but rather embedded within GPAC as a foundational capability, serving as the underlying infrastructure supporting semantic computation and intelligent services. This paper focuses on the adaptation pathways and feasibility of GPAC in key library service scenarios, including the reconstruction of semantic search and recommendation services, the optimization of knowledge organization driven by intelligent metadata, and resource acquisition mechanisms oriented toward knowledge structures. The study demonstrates that GPAC is not merely a continuation of technological evolution of catalog systems but also a vital foundation for reimagining the philosophy and functions of library knowledge services. It offers both a theoretical framework and practical direction for building the next generation of intelligent, trustworthy, and collaborative public knowledge infrastructure.

Based on large language model(LLM) technology, this paper addresses the demand for intelligent upgrading of the Quan Guo Bao Kan Suo Yin(CNBKSY) platform and proposes an intelligent retrieval system integrating natural language processing(NLP), semantic retrieval, and intelligent Q&A. The system aims to overcome the limitations in traditional systems , such as low retrieval efficiency and insufficient recall and precision. It embodies three key innovations. First, it constructs a unified knowledge representation model by integrating heterogeneous data from multiple sources, overcoming format inconsistencies among literature resources and achieving a significant transition from keyword matching to semantic understanding. Second, the system employs advanced vectorization models such as BERT and BGE, combined with hybrid retrieval strategies including BM25 and Solr-based methods, to achieve precise and efficient document retrieval. Third, the system incorporates an intelligent Q&A module, supporting multi-round natural language search and high-precision question answering. Thetest results demonstrate that the system achieves significant improvements over traditional retrieval methods in terms of efficiency, recall, and precision, providing a viable technical solution for the intelligent development of the CNBKSY platform.

This paper aims to address the high manual costs and insufficient accuracy associated with the current construction of intangible cultural heritage(ICH) knowledge graphs by proposing a new approach using the large-scale pre-trained model ChatGPT. Specifically, we propose a domain knowledge graph construction framework, ChatKG(Chat Knowledge Graph), based on large language model and prompt engineering. By reusing the CIDOC CRM ontology model and combining manual curation with ChatGPT-assisted knowledge extraction, the framework enables the construction of ontologies for intangible cultural heritage. Additionally, we propose a Chain of Thought(CoT) prompt optimization method for accurate knowledge extraction. This provides a rapid, efficient, and low-cost solution for building domain ontology models and extracting knowledge in the ICH field, which originally lacks reusable ontology concept models and high-quality annotated data. Taking the Chinese intangible cultural heritage ceramic craft as an example, the model successfully identified 419 craft entities and 763 relationships between entities, ultimately constructing a knowledge graph and exploring application scenarios, thereby validating the effectiveness of our method.

Historical geographic data provide spatial-temporal context for events involving historical figures. The effective organization and utilization of such data can deepen the semantic associations of classical texts. Taking the Book of Han(Han Shu) as the research object, the study explores how historical geographic data can support the organization and analysis of historical documents. By utilizing the China Historical Geographic Information System(CHGIS), historical place names and administrative division evolution data are obtained to construct a cross-temporal place-name knowledge base. Based on the event information extraction paradigm, it compares the applicability of traditional pretrained language models and large language models in detecting event information in classical Chinese texts. The GijiBERT-BiLSTM-CRF model is employed to extract event sentences from the biographies in the Book of Han and to annotate the event types. Using classical Chinese part-of-speech tagging and rule-matching methods, the study further extracts place names from the event sentences. A neural network and the toponym knowledge base are then employed to link the place names to entities, aggregating event sentences that refer to the same place under different names. CHGIS is used to visualize the spatial distribution of different types of events. A total of 18,525 event sentences were extracted from the biographies in the Book of Han. Through toponym entity linking, 1,253 event sentences were spatially located. Using place names as retrieval points for event information increased the recall rate to 1.3 times the original level. Visualization based on digital maps also improved the readability of historical data. This study validates the potential of historical geographic data in organizing and analyzing event information in ancient texts, providing a practical methodological reference for spatio-temporal association mining in historical documents.

Based on the health-related texts from WeChat public accounts, the study conducts feature mining to explore how to effectively improve the accuracy of false health information detection, enhance the quality of healthy information on online platforms, and provide reference for users to make health-related decisions.Starting with four dimensions—content features, emotional features, publisher features and domain features, this paper proposes a health misinformation recognition method based on multidimensional feature fusion and multi-layer perceptron method(MDFF-MLP). Firstly, the textual content is analyzed to extract multidimensional key features. Secondly, feature ablation experiments are conducted to determine feature combinations with rich meaning and strong ability to distinguish true and false information. The sentiment lexicon in the dietary health domain is optimized, and a multilayer perceptron model based on the multi-dimensional fusion of “content-emotion-publisher-domain” features is constructed. Finally, a deep belief network is used to learn multidimensional features and classify dietary health misinformation. The findings indicate that in the MDFF-MLP model, the discriminative power of single-dimensional features reaches 0.90 for content features and 0.84 for publisher features. After multidimensional feature fusion, the model achieves an accuracy of 0.96, with an F1 score of 0.95. Compared with baseline models such as Logistic regression(F1=0.82) and LightGBM(F1=0.89), this model demonstrates significant improvement and strong practical applicability. 

This study explores the similarities and differences in online health information needs between surrogateseekers and self-seekers. The aim is to enhance the consultation efficiency of surrogate-seekers, assist internet healthcare professionals in optimizing consultation processes for different users, and enable online healthcare platforms to provide differentiated services based on user characteristics. Using the TextRank algorithm, this research extracts keywords from online consultation texts and refines information needs based on the ERG theory. Through manual coding, key terms and themes are identified for thematic analysis to construct online consultation behavior patterns. The study examines the online health information needs and behavior patterns of the two user groups, categorizing their information needs into eight dimensions, including consultation needs, treatment needs, and medication needs. The findings reveal that self-seekers pay significantly more attention to prognostic needs than surrogate seekers and express more prominent negative emotions. Additionally, the triggering mechanisms underlying interval behaviors and waiting behaviors differ between the two user groups in their online consultation behavior patterns.