[Purpose/Significance] In the era of data elements, the innovation in public data development and utilization has promoted the development of new quality productive forces. Exploring its innovation mechanism is conducive to unlocking the value of public data. [Method/Process] Focusing on the innovation mechanism of public data development and utilization, and based on grounded theory, interviews and data coding analysis were conducted with 18 innovation participants. Consequently, an innovation mechanism model for public data development and utilization was constructed, covering 4 core categories, 12 main categories, 46 basic categories, and 170 initial concepts. [Result/Conclusion] The research finds that the innovation in public data development and utilization is a dynamic process of “trigger-evolution-regulation-guarantee”, which includes four stages: idea generation, refinement and verification, implementation support, and implementation diffusion. Its influencing factors include innovation-triggering factors, innovation-regulating factors, and innovation-guaranteeing factors. The research systematically analyzes the process logic and operational mechanism of each element in the innovation in public data development and utilization, providing a theoretical framework and practical guidance for deepening the development and utilization of public data.

[Purpose/Significance] The rapid advancement of digital technology has led to an information explosion, while also triggering widespread digital hoarding behavior. As a core group in knowledge production, researchers are particularly prone to falling into digital hoarding. Given that time pressure is a common challenge faced by this group and often elicits two distinct types of responses, gaining deeper insight into the pathways through which time pressure influences researchers’ digital hoarding can help reveal its underlying mechanisms and provide a theoretical basis for effectively mitigating this phenomenon. [Method/Process] Based on an empirical analysis of 400 valid questionnaires from researchers, we examines the mechanisms through which challenge-hindrance time pressure affects digital hoarding behavior among researchers, and tests the moderating role of data literacy in this relationship. [Result/Conclusion] The results showed that: challenging time pressure negatively affects researchers’ digital hoarding, and cognitive absorption fully mediates the mechanism of challenging time pressure on digital hoarding; threatening time pressure positively affects researchers’ digital hoarding, and research emotional exhaustion fully mediates the mechanism of threatening time pressure on digital hoarding. In addition, the moderating effect of data literacy was significant, and the negative effect of cognitive absorption on digital hoarding was stronger when the level of data literacy was higher. This study reveals the path of time pressure on the digital hoarding behavior of researchers, which enriches and expands the existing research in the field of digital hoarding behavior, and also provides theoretical basis and practical suggestions for alleviating digital hoarding of researchers.

[Purpose/Significance] This study explores the cognitive characteristics of users in AIGC multi-modal information search, aiming to provide references for optimizing AIGC multi-modal search tools and enhancing users’ search capabilities. [Method/Process] Based on the Revised Bloom’s Taxonomy, this study collected data through experimental methods. Empirical analyses were conducted using two-way analysis of variance, one-way analysis of variance, paired-samples t-test, Kruskal-Wallis test, Spearman correlation analysis, and multiple linear regression. Focusing on user cognition in the process of multi-modal information search under the AIGC context, the study proceeded along two lines of inquiry.First, it examined the effects of perceived task difficulty, task type, task context, and familiarity on cognition. Second, it investigated the influence of cognition on multi-modal search behavior and outcome satisfaction. Drawing on cognitive psychology theories, the study further analyzed the underlying generative mechanisms and constructed a cognitive process model linking multimodal information stimuli to outcome satisfaction. [Results/Conclusion] First, the perceived difficulty of image tasks is lower than that of video and music tasks. In image search tasks, the cognitive dimensions of remembering, applying, and analyzing are significantly higher than those in video and music tasks. Task context has no significant effect on cognition, while familiarity with image and music tasks is positively correlated with users’ cognition. Second, applying and evaluating positively affect the number of searches, while creating is more associated with long-term search behavior. In addition, understanding, applying, and analyzing positively affect outcome satisfaction.

[Purpose/Significance] International Artificial Intelligence (AI) alliances serve as crucial platforms for promoting the integration of artificial intelligence resources and fostering collaborative innovation. Analyzing their systemic structures can provide strategic references for the development of similar alliances in China. [Method/Process] Drawing on the triadic structural model of information ecology theory, this paper constructed an analytical framework from three dimensions: ontology, subject, and environment. By integrating thematic analysis with tools such as ArcGIS and Gephi, it systematically examined the core topics, member composition, and operational foundations of international AI alliances. Furthermore, it extracted the synergistic interaction mechanisms among the elements of the information ecology. [Result/Conclusion] International AI alliances, grounded in technological infrastructure and knowledge resource sharing, have formed six major core themes. The alliance members mainly consist of four types of entities, i.e. enterprises, non-profit organizations, research institutions, and government or public agencies. The institutional environment plays a dual regulatory role in alliance operations, while the social environment may subtly influence their value orientation. The evolution of alliance forms is closely tied to generational leaps in technology and exhibits a “center-periphery” spatial distribution pattern. There are three types of interactions among information ecological elements: horizontal, vertical, and cross-dimensional. Based on these findings, the future development of AI alliances in China should focus on introducing diverse members to enhance subject density, providing targeted policy support to optimize the information environment, and advocating for an open-source culture to facilitate information flow. These efforts will help strengthen China’s competitiveness and discourse power in the global AI arena.

[Purpose/Significance] Obliteration by incorporation (OBI) refers to the phenomenon where methods, theories, and other forms of knowledge cease to be explicitly cited after becoming widely accepted as common knowledge. This process results in an underestimation of the academic influence of such knowledge, posing challenges to the accuracy and validity of academic evaluation. Therefore, in-depth research on this phenomenon and its underlying mechanisms is important to enhance academic assessment frameworks. [Method/Process] Utilizing the arXiv repository as the data source, this study measures the extent of OBI in physics by analyzing the trends of explicit citations, implicit citations, and citation rates. It then calculates semantic evolution indicators of knowledge phrases from multiple dimensions. A multiple regression analysis is applied to explore the associations between semantic evolution and OBI. [Result/Conclusion] The findings reveal a temporal delay between the peaks of explicit and implicit citations. The reduction of semantic variation, coupled with the enrichment of application contexts, facilitates the transition of knowledge phrases into common knowledge, leading to an increased degree of OBI. This study explains the mechanism underlying OBI from the perspective of semantic evolution, thereby contributing to a deeper understanding of OBI and offering valuable insights for refining citation-based academic evaluation systems.

[Purpose/Significance] Against the backdrop of intensifying global technological competition, how to effectively identify and predict underdeveloped technical fields and untapped technical opportunities in technological development remains an urgent problem to be solved. [Method/Process] This paper proposed a national science and technology intelligence analysis framework based on technology control policies texts. By integrating prompt engineering for large language models (LLMs) and generative topographic mapping (GTM), it constructed GTM patent maps and multi-dimensional GTM maps to mine underdeveloped technology nodes and technological gaps. Then, it designed a multi-dimensional evaluation index system and conducted a comprehensive assessment to identify the technological opportunity points with CRITIC method. Ultimately, inverse mapping technology was utilized for technological interpretation. [Result/Conclusion] Taking the lithography technology clauses in the Commercial Control List as an empirical case, the framework identifies 6 underdeveloped key technology nodes and 3 potential technological innovation opportunities in China, and verifies its scientificity and effectiveness. This framework is intended to provide scientific basis for the formulation of science and technology policies, and technology strategy layout of relevant departments.

[Purpose/Significance] Given contemporary society’s strong demand for digital intelligence technology and knowledge management, the issue of ‘knowledge variation’ within the ‘digital intelligence innovation ecosystem’ has become increasingly important. Consequently, research on knowledge variation mechanisms aimed at ‘knowledge creation’ has become more prominent. [Method/Process] From the dual perspectives of knowledge evolution theory and social epistemology, this study explores the intrinsic logic of knowledge variation in the digital intelligence innovation ecosystem from both dominant logic and constructivist logic. Subsequently, based on cusp catastrophe theory, a cusp catastrophe model of knowledge variation is constructed. This model uses the degree of knowledge entropy within the ecosystem as the state variable, and the external information flow that forms new knowledge and the coherent effects among internal elements as control variables. Finally, the study conducts an empirical analysis of the model. [Result/Conclusion] The study reveals that in the digital intelligence innovation ecosystem, knowledge generation undergoes abrupt state change. The process of catastrophic knowledge generation is a process in which knowledge elements experience giant fluctuations from nonlinear interactions reinforced by sufficient information within the system. The process is characterized by abruptness and randomness, and can be divided into three stages: triggering, evolution, and stabilization.

[Purpose/Significance] This study proposes an intelligent generation method for patent technology function matrices based on large language models. It aims to enhance the efficiency and accuracy of matrix construction and support intelligent intellectual property analysis. [Method/Process] First, the BERTopic model is utilized for deep semantic embedding and nonlinear dimensionality reduction of patent texts, generating hierarchical technology topics with dynamic granularity. Then, a two-round question-and-answer dynamic generation mechanism is designed based on the DeepSeek-R1 model to extract and optimize technology function phrases, forming a hierarchical and structured function dimension system. Finally, a technology function matrix is constructed through co-occurrence analysis and subsequently validated through tests for coverage, accuracy, and reliability. [Result/Conclusion] An empirical study on humanoid robots patents demonstrates that the proposed method performs well in core indicators such as technology function coverage, accuracy, and reliability. The introduction of dynamic granularity adjustment mechanisms and the collaborative optimization of prompt engineering and hierarchical clustering can provide support for intellectual property intelligent analysis, offering fine-grained analysis and trend insight capabilities.

[Purpose/Significance] By applying a range of algorithms and strategies, this study explores technical approaches of entity matching for Chinese homonymous authority records. It aims to provide a framework for the association and integration of the same individual within or across databases. By combining large language models with rule-based matching, an entity matching solution for authority records with duplicate names has been proposed. This solution is designed to reduce data redundancy and facilitate the integration of data in Chinese name authority database. [Method/Process] Personal name authority records with high repetition rate were selected as the analysis samples. Using GPT-4o, entity features were extracted from fields such as notes and reference data sources according to specific rules. Embedding vectors were calculated using a Chinese large language model. Four entity matching schemes were designed by combining techniques such as longest common substring matching, semantic distance matching, and hierarchical clustering. These schemes include: prompt + full-field embedding, single-field embedding weighting, longest common substring + semantic match count, longest common substring + semantic distance weighting. [Result/Conclusion] The experimental results show that “longest substring + semantic matching count” and the “single-field embedding weighting” method perform best in terms of F1 score, with high recall and precision. This makes them suitable for entity matching in library homonymous authority records.

[Purpose/Significance] In the digital era, the deep integration of culture and technology serves as a crucial driving force for the development of new cultural formats. Exploring the inherent logic, existing challenges, and development in the evolution of emerging cultural industries from the perspective of cultural data lifecycle helps the modernization and transformation of the cultural industry. [Method/Process] Based on digital lifecycle theory, a double-helix model encompassing data flow and cultural value dimensions was constructed to analyze cultural data as a “culture-technology” fusion product. The investigation focused on how to achieve efficient circulation, value extraction, and risk management throughout the cultural data lifecycle phases: generation & collection, organization & processing, storage & management, mining & analysis, sharing & dissemination, and preservation & obsolescence. [Result/Conclusion] The study proposes a development pathway for new cultural formats through four coordinated dimensions: the government’s multiple role positioning, the development of new cultural enterprises, research-based think tank support, and open user participation. These findings provide practical recommendations for promoting deeper integration between cultural development and technological advancement.

[Purpose/Significance] Digital preservation ensures that large-scale, growing digital information resources remain understandable and usable over time. Systematically reviewing and deconstructing domestic achievements in digital preservation is of great significance for clarifying the research and development trends in this field. [Method/Process] This study selected literature from CSSCI (Chinese Social Sciences Citation Index) as the data source. It employed the LDA model to classify the research themes and analyzed application scenarios, risks and governance, and technological development from both longitudinal and cross-sectional perspectives. [Result/Conclusion] Digital preservation has made notable progress in scenarios such as the maintenance of social memory, digital resource management, and data application services, with the technology now transitioning into an intelligent development stage. However, it also faces risks at the technological, ethical, and economic levels. These risks should be managed by exploring a dynamic risk identification system, establishing a systematic legal protection framework, and constructing a diversified funding assurance mechanism.

[Purpose/Significance] Empowering traditional ancient book restoration by modern science and technology is an inevitable choice for the high-quality development of ancient book restoration cause. Analyzing and assessing the development dilemmas, feasible strategies, and future directions of ancient book restoration science and technology can provide both theoretical and practical guidance for its scientific transformation and modernization. [Method/Process] By adopting literature research and online investigation methods, this study systematically sorts out the current development status of ancient book restoration science and technology in China, identifies existing dilemmas, extracts corresponding strategies, assesses future directions, and comprehensively constructs a development framework for the field. [Result/Conclusion] China’s ancient book restoration science and technology has achieved progress in seven key areas: preservation and transmission of restoration knowledge, construction and control of restoration spaces, understanding and treatment of restoration objects, preparation and testing of restoration materials, application and research and development of restoration tools, cultivation and development of restoration talents, and collaboration and innovation in restoration research. However, practical dilemmas stillexist, including the inherent conflict between craftsmanship inheritance and technology intervention, structural constraints of talent cultivation paradigms and talent introduction mechanisms, and the field barriers to cross-boundary linkage and interdisciplinary integration. Feasible countermeasures include accelerating the popularization of technological concepts, focusing on the development of scientific and technological talents, and deepening scientific research collaboration and exchanges. Looking to the future, priorities should be the integration of traditional craftsmanship with modern technology, the promotion application of digital and intelligent restoration technologies, and the establishment of a collaborative and shared system for ancient book restoration.