Special Topics

1 Intelligent Information Technology: Connotations, Boundaries, and Frameworks Yao Changqing, Cheng Qikai, Wang Lijun, Liu Jiawei DOI: 10.3772/j.issn.1000-0135.2025.01.001 Information has undergone a profound transformation from traditional to intelligent models. From early intelligent retrieval to the current large-model-driven intelligent information understanding, information technologies have gradually evolved from ‘Intelligence + Information’ and ‘Intelligence for Information’ into new paradigms of ‘Intelligence as Information’ and ‘Information is Intelligence.’ This study thoroughly explores the concept, technical boundaries, and systematic construction of intelligent information technology, proposing a system architecture tailored to the digital intelligence era. This framework encompasses collaborative sensing and integration technologies for all-source scientific and technological information, cognitive understanding technologies for intelligent information, monitoring and early warning technologies for intelligent information, intelligent analysis technologies for competitive intelligence, and scientific-information-driven intelligent evidence-based decision-making technologies. This system comprehensively addresses all processes of information work, aiming to enhance information and research capabilities through system construction, support the intelligent transformation of scientific information endeavors, and contribute to China’s high-level self-reliance and strength in science and technology. The research presented in this paper not only holds significant theoretical value for the advancement of intelligent information technology but also provides a clear technical roadmap and implementation framework for practical applications. 2025 Vol. 44 (1): 1-9 [Abstract] ( 27 ) HTML (71 KB)  PDF (1379 KB)  ( 72 )

Intelligence Theories and Methods

10 Transmission Pathways of Major Emergencies Based on Event Evolutionary Graph Zhang Chunlong, Zhang Haitao, Pang Yufei, Yang Yi, Zhang Kexin DOI: 10.3772/j.issn.1000-0135.2025.01.002 Starting from scientifically responding to major emergencies, this study focuses on intelligence and wisdom, and utilizes theories such as event evolutionary graphs and network science to clarify the conceptual implications of driving factors, transmission pathways, and coupling models of major emergencies. It constructs a transmission pathway and coupling model for major emergencies, further revealing the evolutionary mechanisms of these events. Based on theoretical research, a specific process of building a major emergency transmission link and a transmission link coupling model is proposed. Based on rainstorm data from the past three years, a rainstorm event transmission link and a transmission link coupling model are constructed, and the coupling mechanism between the event transmission link, public opinion transmission link, and emergency transmission link in rainstorm events is revealed. Then, the scientificity of the conduction link and coupling model, and the operability of the construction method and process are verified. Based on empirical research results and following the concept of system science, this paper discusses the application scenarios of major emergency transmission pathways and coupling models, which is of great significance for building a “risk management - public opinion management - emergency management” tripartite decision-making and emergency management system for major emergencies. 2025 Vol. 44 (1): 10-19 [Abstract] ( 7 ) HTML (93 KB)  PDF (4152 KB)  ( 39 )

20 Identification Methodology Research for Breakthrough Technological Innovations Based on Dynamic Complex Networks Zhou Wenhao, Wu Bingyi, Li Hailin, Wang Panxi DOI: 10.3772/j.issn.1000-0135.2025.01.003 Identifying and anticipating breakthrough technological innovations is critical for precisely implementing technological interventions and accelerating the formation of new quality productive forces. However, traditional single-measurement indicators cannot fully reflect the rich connotation and multidimensional characteristics of breakthrough technological innovations. Based on the theory of technological leap and knowledge recombination theory, this study constructed a novel two-stage identification method for breakthrough technological innovations based on a dynamic patent similarity network. It comprehensively examined two characteristics: the source of technological novelty and the impact of technology. The empirical study of 61431 authorized patents from 982 Chinese manufacturing enterprises successfully identified 3738 breakthrough technological innovations, accounting for 6.085%. Among them, independent and knowledge recombination breakthrough technologies accounted for 3.488% and 2.596%, respectively. Further, topic models were used to refine the main research fields and directions of breakthrough technological innovations. The effectiveness and robustness of the identification results were comprehensively verified by combining economic consequences, typical technology cases, technology field evolution cases, and multiple statistical models. The research findings provide a feasible identification framework and tools for breakthrough innovation-related research and technology foresight and technology policy formulation on the practical level. 2025 Vol. 44 (1): 20-34 [Abstract] ( 6 ) HTML (210 KB)  PDF (3234 KB)  ( 34 )

35 Inventor Mobility and Team Dual Innovation: An Impact Analysis of Knowledge Complementarity and Knowledge Substitutability Wang Jiajie, Wang Tao, Sun Jianjun DOI: 10.3772/j.issn.1000-0135.2025.01.004 The mobility of inventors and the resultant impact on team innovation performance have garnered significant attention in academia. However, limited research exists on how inventors’ knowledge integrates with new team knowledge networks and how this coupling affects exploratory and exploitative innovation. Using a sample of 108,468 inventor mobility cases from the European Patent Office’s global patent database, this study measures the levels of knowledge complementarity and substitutability between inventors and new teams from the perspective of knowledge coupling. Using a negative binomial regression model, the results posit that (1) knowledge complementarity between inventors and new teams positively correlated with team exploratory innovation but negatively correlated with exploitative innovation; (2) knowledge substitutability positively correlated with exploitative innovation and negatively correlated with exploratory innovation; and (3) team knowledge breadth weakens the positive relationship between knowledge substitutability and team exploitative innovation while enhancing other related effects. These findings advance theoretical understanding of the innovation mechanisms underpinning knowledge transfer through talent mobility and offer practical insights into inventor mobility, team innovation collaboration, and related policy formulations, providing a reference for the development of talent hubs and innovation ecosystems. 2025 Vol. 44 (1): 35-47 [Abstract] ( 10 ) HTML (189 KB)  PDF (1584 KB)  ( 13 )

48 Recommendation Method for Enterprise R&D Partners Using Technology Matching and Typological Optimization Zhao Zhanyi, Zhong Yongheng, Li Zhenzhen, Liu Jia, Xi Chongjun DOI: 10.3772/j.issn.1000-0135.2025.01.005 Accurately recommending compatible partners among diverse innovation entities is crucial for reducing innovation risks and overcoming key core technological challenges. This study proposes a method for recommending enterprise R&D partners based on technology matching and typological optimization to enhance precision and interpretability. The method integrates technological matching, including technological similarity and complementarity to identify large-scale potential cooperation pairs using machine learning algorithms. The Boston Matrix is employed to categorize these recommendations across two dimensions: technological similarity and complementarity. Additionally, indicators such as innovation strength, cooperation preferences, proximity, and brand effect are combined to evaluate the typological results and optimize the entire process. Using the field of fuel cells for an empirical application, the results depict that the model's identification algorithm achieves an F1 value of 93%, outperforming category and semantic dimensions-based algorithms by 2 and 4 percentage points, respectively. This model accurately reflects technological matching between innovation entities and supports the subdivision of partners into four categories: priority cooperation, key focus, transformative complement, and diversified expansion. The evaluation and optimization results can effectively distinguish and provide various options for enterprises, increasing the likelihood of successful cooperation. 2025 Vol. 44 (1): 48-60 [Abstract] ( 15 ) HTML (191 KB)  PDF (2760 KB)  ( 15 )

61 Research on the Collaborative Mechanism of Medical Data Sharing Stakeholders: Based on Quadripartite Evolutionary Game Analysis Zhang Meng, Mu Dongmei, Deng Jun, Wang Ping, Li Yin DOI: 10.3772/j.issn.1000-0135.2025.01.006 In the medical data-sharing process, the balance of interests among various subjects is the key to promoting the collaborative participation of stakeholders. Thus, the construction of the collaborative mechanism of medical data sharing is conducive to its optimal development. Based on the evolutionary game theory, the benefit matrix was constructed from the perspective of the dynamic distribution of interests. The replication dynamic equation was then used to analyze the game strategy selection mechanism driven by interests, whereas the influence of key factors on system evolution was analyzed using MATLAB R2023a simulation. From the initial stage of simulation to the mature stage, medical data sharing underwent 12 stable strategy points of the evolutionary game, whereas the cooperation evolution process of various subjects exhibited dynamic characteristics. Strong government supervision can effectively promote the collaborative participation of stakeholders in medical data sharing. Furthermore, reducing the cost of strong supervision has a significant positive impact on the strategy selection of the government and medical institutions providing data. The government's subsidy coefficient for medical institutions and the rewards and punishments for medical data centers positively drive medical institutions to provide medical data, in addition to reducing the risk of medical data sharing. The cost and benefit of data sharing by medical institutions substantially impact the strategy selection of medical data providers, and the influence degree varies in different configurations. 2025 Vol. 44 (1): 61-74 [Abstract] ( 6 ) HTML (258 KB)  PDF (3895 KB)  ( 18 )

Intelligence Technology and Application

75 Interdisciplinarity of Information Resources Management: An Analysis Based on Multi-label Classification Liu Qingmin, Wang Fang DOI: 10.3772/j.issn.1000-0135.2025.01.007 In contemporary society, there are numerous complex, diverse, and interconnected problems that cannot be fully addressed within in a single discipline. Hence, interdisciplinary studies integrate knowledge, theories, methods, and technologies from multiple disciplines to address ambiguous and complex issues. To reveal the interdisciplinary trends and characteristics of research in the field of information resource management, this study uses the Chinese Library Classification Number (CLCN) as the basis for subject classification. Addressing inaccuracies in CLCN annotations provided by authors, the study employs large language models for data augmentation and optimization and applies a BERT-CNN algorithm to refine the CLCN. A systematic analysis of the literature in the field of information resource management is conducted. Regarding interdisciplinary diversity, two new metrics—inclusiveness and permeability—are proposed to measure the knowledge absorption capacity and diffusion influence among disciplines. The use of CLCN codes to mine and analyze high-frequency, continuous cross-disciplinary research themes and emerging hot topics has revealed the rapid development of emerging fields such as health informatics and digital humanities, as well as the ongoing interdisciplinary research. The results show that the field of information resource management presents a rich and diverse disciplinary pattern, with each discipline closely connected and influencing each other; its development is the result of the cross-integration of multiple disciplines. Interdisciplinary research is on the rise and plays an important role in information resource management. The establishment of guiding secondary disciplines has demonstrated rationality and effectiveness in terms of theoretical foundation, practical application, and interdisciplinary cooperation. 2025 Vol. 44 (1): 75-92 [Abstract] ( 19 ) HTML (205 KB)  PDF (3268 KB)  ( 29 )

Intelligence Discipline Development and Construction

93 Discernment of the Concept of Information Resources and Its Logical Relationship with the Information, Data, and Knowledge Ye Jiyuan DOI: 10.3772/j.issn.1000-0135.2025.01.008 Information resources are crucial strategic assets for economic and social development. However, the concept of information resources has long been based on narrow and broad definitions popularized abroad, resulting in ambiguity and frequent confusion with related concepts, such as information, information management, and information systems. This confusion hinders both theoretical research and practical applications. This study employs concept analysis, keyword analysis, and comparative research to clarify the concept of information resources, reveal their characteristics, and support the theoretical and practical development of disciplines such as information and information resource management, information economics, information sociology, journalism and communication, and computer science. By thoroughly absorbing the reasonable core of the various definitions, a new definition of information resources is proposed: information resources are all carriers (including the human brain) that record meaningful, exploitable, and usable epistemological information. These include data, knowledge, and wisdom resources. This new definition integrates and transcends the narrow and broad definitions, identifying the characteristics of information resources such as being carrier-based, scalable, demand-driven, communicable, transformable, shareable, and relative. Case studies demonstrate the new definition’s superior explanatory power and verifiability. They also clarify how the logical relationships between information resources and information, data, knowledge, wisdom, intelligence, and documents, in addition to laying a theoretical foundation for the better development and utilization of information resources. 2025 Vol. 44 (1): 93-102 [Abstract] ( 11 ) HTML (73 KB)  PDF (1163 KB)  ( 43 )

Intelligence Reviews and Comments

103 Temporal Networks: Concept, Application, and Perspective Wu Jiang, Yu Yang, Ding Honghao, Tao Chengxu, Zuo Renxian, He Chaocheng DOI: 10.3772/j.issn.1000-0135.2025.01.009 As a representation that captures dynamic interactions, temporal networks can provide an accurate depiction of dynamic systems in fields such as network public opinion and scientific collaboration. Because the application of temporal networks in these areas is in its nascent stage, this study systematically reviews the use of temporal networks in information science. First, a detailed introduction to the concept and research methods of temporal networks is provided. Specifically, their definitions are presented, metrics for structural types and output granularity are proposed, and the origins and development of temporal-network research methods are explained. Second, a keyword co-occurrence network and topic-clustering analysis is conducted on existing studies to identify the current research hotspots and application scenarios for temporal networks in information science. Third, based on existing application scenarios, this study analyzes the related findings in five areas of information science: scientific collaboration and scientometrics, medical informatics and health informatics, information recommendation and digital humanities, network public opinion and social media, and emerging technologies and smart cities. Finally, future research directions for temporal networks in information science are proposed from macro-, meso-, and micro-perspectives, thus providing insights for studies related to temporal networks in this domain. 2025 Vol. 44 (1): 103-122 [Abstract] ( 9 ) HTML (244 KB)  PDF (5818 KB)  ( 44 )