[Purpose/significance]Intangible cultural heritage is an important component of human civilization, which is of great significance for protecting and promoting national spirit, enhancing national identity and cohesion. [Method/process]This paper explores how to utilize the advantages of  AIGC, combined with traditional deep learning methods, then construct a comprehensive and efficient map of intangible cultural heritage knowledge. [Result/conclusion]In the classification study of intangible cultural heritage projects, the fine-tuned Baihuan-7B has the best effect, with an macro-F1 value of 0.7688. In the extraction of intangible cultural heritage attribute information, RoBERTa has the best effect, with an F1 value of 0.7085. The 2-Gram BLEU generated by fine-tuning Baihuan-7B is 0.2052. Combining the results of attribute extraction and generation, an efficient and comprehensive knowledge graph is constructed. [Innovation/limitation]This study uses a generative large model to assist in the establishment of knowledge graphs, focus on national-level intangible fruit projects, not induding provinciul-level projects with high reasearch value.

[Purpose/significance]By combining knowledge graph representation learning and word representation learning,this paper explores the question answering model based on knowledge graph,so as to realize the utilization of structured knowledge with high accuracy and wide coverage in the knowledge graph.[Method/processe]This paper proposes a knowledge-based QA system,a framework integrating knowledge graph representation learning and word representation learning,and uses comparative and empirical research to explore the influence of different representation learning models and network structure on the effect of knowledge-based QA system.Firstly,the knowledge graph representation learning algorithm is used to generate the vector representation of entities and relations. Secondly,the generated entity and relation vectors are used as supervisory signals to train the vector representation of the problem.Finally,the best answer of the matching problem in the knowledge graph is selected by the triple representation generated by the problem.[Result/conclusion]The experimental results show that different representation learning model and network structure have a significant impact on the effect of knowledge-based question answering.Compared with the baseline method,this method can significantly improve the effect of knowledge base question answering.The research plays an important role in promoting the application of deep learning in the research of knowledge-based question answering.

[Purpose/significance]Identifying and foreseeing emerging technologies, bring technological first-mover advantages to enterprises and governments, and grasp technological development trends in a timely manner. [Method/process]This study uses BERTopic's topic modeling method to obtain domain topic distribution, and merges paper and patent topics based on the cosine similarity of topic vectors to identify emerging topics. [Result/conclusion]Using the BERTopic topic modeling method combined with index evaluation can effectively identify emerging topics and emerging terms.Taking the field of new energy vehicles as an example to carry out empirical research, using two methods: divided verification period and data verification method, 12 of the 16 identified topics passed the verification, which verified the effectiveness of this research method.

[Purpose/significance]The main path analysis of citation networks can be used to identify important literature in specific fields and can achieve the extraction of mainstream research threads. This paper will use the main path analysis method to analyze the research path of knowledge graphs and sort out the context of their research development. [Method/process]This paper firstly obtains research papers in the field of knowledge graphs from the Web of Science platform, then uses the HistCite software to generate a direct citation network of the literature, and then imports the data into Pajek to generate multiple main paths of the dataset, and combines the content of the papers on the main paths for qualitative analysis. [Result/conclusion]Through main path analysis, some main paths in the field of knowledge graphs can be quickly identified, such as the construction of knowledge graph, research on the application of knowledge graphs in recommendation and question answering and other application scenarios, research on the application of knowledge graphs in specific application fields such as manufacturing. These paths reflect the development context and research direction of knowledge graph technology. Review studies have played an important role in the development of the knowledge.

[Purpose/significance]Integrity and innovation are important issues that the Institute of Science and Technology Intelligence needs to grasp. [Method/process]Regarding innovative issues based on adhering to principles and starting from historical facts, this article analyzes the role and significance of WIKID memes in scientific and technological intelligence study, explores relevant professional operational standards, proposes to strengthen the ability to compile WIKID memes under strategic concerns, implements intelligence thematic research based on dynamic clue discovery, and carefully examines the norms of meme characterization in perception scanning. [Result/conclusion]These are necessary actions for scientific and technological intelligence professionals and professional institutions to respond to the challenges of the times.

[Purpose/significance]This paper focuses on the viewpoints of leading American think tanks on chip competition with China, aiming to unravel the logic behind the formulation of U.S. chip policies towards China. It also seeks to explore innovative pathways for the development of China's chip industry and provide strategic recommendations beneficial to Sino-American chip competition. [Method/process]The study selects 20 representative research reports from 9 prominent think tanks and employs a literature analysis approach to dissect the viewpoints, motives, and potential influences found in these reports. [Result/conclusion]The results reveal that most American think tanks adopt a firm stance, perceiving the rise of China's chip industry as a threat. Calls for sanctions against Chinese chips dominate the mainstream discourse. In response, China should strengthen its own innovation strategy and actively address the situation through avenues such as deepening Sino-American dialogues for understanding and seeking international multilateral cooperation.

[Purpose/significance]In order to make full use of the value of text dependent syntactic information and prior emotion knowledge in emotion analysis， a semantic enhanced online healthy community emotion analysis model was proposed. [Method/process]Firstly， feature vectors for pre-processed online health community data are generated by Word2Vec and BERT; then local and global information of online review text are extracted using TextCNN and BiLSTM respectively based on dual-channel idea; then sentiment knowledge and dependency grammar information are merged in graph attention networks for semantic enhancement; finally， dual-channel features are fused and perform online health community sentiment classification in fully connected layer. [Result/conclusion]The comparative experiments on 31718 online health community comments show that the accuracy of the BERT-TBGH model based on semantic enhancement reaches 90.77%, which is 10.57% and 7.79% higher than the classical models TextCNN and BiLSTM and is 1.85% and 1.00% higher after introducing sentiment knowledge and character-level dependency syntactic information. The proposed model based on semantic enhanced BERT-TBGH model can effectively improve the effect of online healthy community emotion analysis. The defect of this article is that the experiment was limited to the online health community dataset and was not further validated on larger datasets.

[Purpose/significance]With the strong ability to process large-scale datasets and outstanding performance in various natural language processing tasks, large language models （LLMs） have excelled across multiple industries. Since scientific and technical intelligence primarily relies on textual data, LLMs are naturally well-suited for this field, ushering in a new wave of transformative changes. [Method/process]This article discusses the advantages of LLMs from five perspectives: low-dimensional dense vector representations of text, large-scale pre-trained models, fine-tuning and prompt learning, high-quality large-scale training data, and human alignment techniques. [Result/conclusion]LLMs have extensive applications in tasks such as intelligence identification, intelligence tracking, intelligence evaluation, and intelligence prediction, resulting in significant optimization improvements or paradigm shifts.

[Purpose/significance]Biosecurity intelligence plays an important role in promoting the development of bio-medication industry, and it will contribute to the in-depth development in this field by sorting out the research issues of Biosecurity intelligence. [Method/process]Firstly, the concept and classification of biosecurity intelligence are elucidated. Following this, from the foundational theories of intelligence studies and biosecurity science, the application of these theories in the work of biosecurity intelligence is analyzed. Subsequently, an overview is provided of research on biosecurity intelligence work geared towards biosecurity governance within China, alongside which the challenges faced by such work in our country and corresponding strategies are put forward.[Result/conclusion]Future Biosecurity intelligence work needs to progress from being fragmented to interconnected, and from scattered to comprehensive, driving the development of the Biosecurity intelligence system. On one hand, attention should be given to the application and innovation of advanced science and technology, as well as tools and methods, in biosecurity intelligence work. On the other hand, strategic positioning and legal affirmation must be provided at the institutional level, fostering the formation of synergistic forces for implementation, enabling the biosecurity intelligence work system to evolve from differentiation toward integration. 

[Purpose/significance]This paper attempts to sort out the development context of the field of knowledge organization, its evolution law and the driving factors of evolution, expounds the new needs and tasks of knowledge organization of scientific and technological information institutions in the era of big data and the innovative exploration of scientific and technological information community.[Method/process]This paper preliminarily investigates the research progress, challenges and shortcomings in the digitalization-intelligentize of knowledge organization in recent years, predicts the future development trend and ideas, and emphasizes the need to take the road of combining professional elite with grassroots, human intelligence and data intelligence. [Result/conclusion]Several areas that need to be paid attention to and strengthened in the development of knowledge organization in the library and information community are proposed, namely, data labeling, organization and retrieval of datasets, and metadata in data management.

[Purpose/significance]Digital rule of law government is a new paradigm of government governance that is compatible with digital China and digital society. Data elements have become an important driving force for high-quality economic development in the era of digital, and public data openness is an important issue in the construction of digital rule of law government. [Method/process]In this paper, the regulations, policies and technical standards of the central government and 10 provinces, including Zhejiang, Shandong, Guizhou, Guangdong, Sichuan, Fujian, Guangxi, Hainan, Jiangxi and Jiangsu as research samples to examine the current system of regulations and policies on the opening up of public data in China, and to review the problems in the opening up of data on this basis. [Result/conclusion]The study finds that there are problems in China's public data opening such as uncertainty in the connotation boundaries, gaps in the regulatory policy system, lack of supply of administrative rule of law system, and immaturity in the mechanism for safeguarding citizens' data rights. In this regard, the concept of public data should be clearly defined and the nature of ownership, the regulatory policy system of public data openness should be improved, the administrative rule of law order of public data openness should be constructed, and the institutional mechanism of guaranteeing citizens' data rights should be improved, so as to integrate the opening up of public data into the track of the rule of law.

[Purpose/significance]This paper explores the guiding role of Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era in the development of the Information Resource Management discipline with Chinese characteristics, providing significant insights for the innovative advancement of China's Information Resource Management discipline and strengthening the discourse power of Chinese social sciences. [Method/process]This paper systematically reviews the core elements of the development philosophy of the Information Resource Management discipline within Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era from a holistic perspective, elucidates the logical system of the development of the discipline from the diverse perspectives of national strategy integration, innovative development paths, and discourse system construction, and summarizes the value implications from both theoretical and practical viewpoints. Based on research papers published in core journals of the Information Resource Management discipline and related policy texts, this paper employs topic mining techniques to analyze the development overview and thematic evolution features of the research in the Information Resource Management field from a concrete perspective. [Result/conclusion]This study results indicate that Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era has provided guidance for theoretical innovation and interdisciplinary integration in the field of Information Resources Management. It has strengthened the discipline's role in supporting and responding to national strategies, offering both theoretical foundations and practical references for the high-quality development of philosophy and social sciences with Chinese characteristics.

[Purpose/significance]To enrich the identification methods of competitors in competitive intelligence strategies under the new situation, and provide decision support for enterprises to formulate technology competition strategies in complex and ever-changing market competition environments. [Method/process]This article using patents as data sources, construct a framework for identifying competitors and conduct empirical research.Firstly, based on the LDA model, identify the main technological research and development directions of the target enterprise and determine the set of candidate competitor enterprises; Secondly, construct a two-dimensional strategic coordinate based on technology and market similarity, and divide the candidate competitor combination of the target enterprise into direct, indirect, and potential competitors; Finally, the patent intensity index based on patent portfolio analysis is introduced to measure the technological competition gap between the target enterprise and its competitors, and to assess the relative competitive situation. This article conduct empirical research targeting Apollo Zhilian (Beijing) Technology Company in the field of intelligent connected vehicles. [Result/conclusion]Based on the competitor identification framework constructed in this article, a total of 5 competitors of Apollo Zhilian (Beijing) Technology Company were identified, including three types. At the same time, an analysis of the relative competitive situation between the target enterprise and its competitors was achieved in various major technological research and development directions. The empirical results indicate that the framework constructed in this article fully considers the technological resource endowment of the enterprise itself, the competitive gap with competitors, and can accurately meet the methodological of requirements of identifying competitors, with good application prospects.

[Purpose/significance]Disruptive technology is regarded as a revolutionary force that "changes the rules of the game" and "reshapes the future pattern", and has gradually become a hot and difficult issue in interdisciplinary research. This paper summarizes the literature related to disruptive technologies, clarifies the concepts and characteristics of disruptive technologies, subdivides research topics and directions, summarizes research focuses and looks forward to future development trends, and provides reference for relevant personnel. [Method/process]On the basis of sorting out the latest related research on disruptive technologies, this paper clarifies the research progress of disruptive technologies from three aspects: the concept and characteristics of disruptive technologies, common identification methods, and the evolution and prediction analysis of disruptive technologies, and grasps the research status and development trend of this field. [Result/conclusion]This paper comprehensively summarized the current research status of disruptive technology, and analyzed the existing problems and shortcomings.