[Purpose/significance]The article reveals the theoretical systems, technological systems, and applied systems of vector databases, aiming to promote innovation in the research and practice of multimodal AI related theories, technologies, and applications. [Method/process]This article elaborates on the evolution of vector databases and defines its core concepts through literatures tracing and content analyzing. Subsequently, it compares and analyzes their characteristics and values, and based on this, sorts out their application mechanisms, functions, corresponding key technologies and application modes. Simultaneously, it discusses the challenges and countermeasures faced by vector databases, and looks forward to their development trends from theoretical, technical, and application perspectives. [Result/conclusion]Vector databases originate from the construction of the vector index method system, develop in vector data retrieval engine construction, and mature in vector database management system construction. Compared to relational databases and graph databases, vector databases exhibit obvious characteristics in data models, indexing mechanisms. They hold various value for users, data managers, developers and researchers. The key technologies are divided into three categories: vector data embedding generation, vector data indexing, and vector data retrieval. Application patterns can be divided into three categories: data-driven applications, knowledge-driven applications and scenario-driven applications. Challenges exist in various aspects such as high-quality generation, semantic description, storage resource utilization, collaborative sharing, and ethical security of vector data. Trends point towards the systematization of theoretical frameworks, maturation of technical solutions, and ecosystem development of application services.

[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]The most prominent feature of the new quality productivity is scientific and technological innovation. In the new era, intelligence plays a new role of eyes and ears, spearhead and staff, and also plays a new role of guidance. This paper analyzes the intelligent revolution of new quality productivity from the perspective of information science, and probes into its challenges and opportunities to traditional intelligence work. [Method/process]New quality productivity takes data as the core element, forms wisdom based on data, enables scientific and technological innovation, and promotes social and economic development. Intelligence work needs to adapt to new productivity and improve efficiency and quality through technological innovations such as intelligent intelligence collection and knowledge graph application. [Result/conclusion]The paper emphasizes the necessity of building a "production relationship" that matches the new productivity, including strengthening organizational management, personnel training and technological innovation. Through the intelligent promotion of new quality productivity in various fields of intelligence, it can promote the high-quality development of social economy.

[Propose/significance]By summarizing the research results of international medical data sharing, this paper provides reference for related theoretical research and sharing practice. [Method/process]This paper tared, CNKI and Web of Science databases were used as data sources, and visualization software CiteSpace was used to draw keywords clustering maps, count high-frequency keywords and cluster label words, and analyze the macro trend of research results in the field of international medical data sharing. Further use the text content analysis method to carry out a systematic analysis of the research hot topics. [Result/conclusion]The research hot topics in the field of medical data sharing can be summarized into five aspects: medical data sharing mode, stakeholders, platform technology, influencing factors, and incentive mechanism. "Blockchain" technology is widely used in the research of medical data sharing field, and plays an important role in the key issues such as platform technology and incentive mechanism, however, the practice of medical data sharing in China is still in the initial stage, and it is necessary to strengthen the theoretical research of medical data sharing, enrich the investigation forms and research paths, and improve the data sharing policies and regulations to promote the practice of medical data sharing.

[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]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]Allusions, as an important and widely used rhetorical device in literary creation, hold immeasurable value for the study of ancient Chinese literature. Despite this, the automatic identification technology for allusions is not yet mature and currently relies mainly on manual identification, which requires further in-depth research. [Method/process]The article proposes an allusion citation recognition method that incorporates the function of making corrections using large language models at the decision-making level. This method combines traditional sequence labeling techniques with general large language models, introduces prompt templates, and performs output fusion at the decision layer to improve accuracy. In addition, this study also constructs a set of evaluation metrics specifically for the problem of allusion identification. [Result/conclusion]Through generalization testing, the AR_BBC_LP allusion identification model performed excellently in the experiment, with P_allu, R_allu, and F1_allu reaching 89.75%, 89.38%, and 89.56% respectively, significantly better than existing baseline models. The results show that the model not only enhances the performance of traditional sequence labeling models but also opens up new areas for the application of large language models. It also provides a new perspective and strong methodological support for the identification of allusions and their application in the study of ancient Chinese literature.

[Purpose/significance]Through teasing blockchain research status and hotpot in library and information discipline,the paper sums up the research achievements and problems, and provides references for the future development of blockchain in the field of library and information. [Method/process]This paper takes CNKI and CSSCI as data source, and analyses the research of blockchain in library and information discipline from the amounts of published papers, author, institute, keyword bursts, cited references. [Result/conclusion]The research shows that blockchain research in library and information area arrived in peak in 2021, and developed with other disciplines. But there are some problems still exist such as the decrease of the amount of papers , the instability of team, the lack of cooperation, the lack of quality paper, based on problems mentioned above, the paper proposes the prospects from the research contents, the research methods ,the cooperation of author and institute, the integrative development of multi-idea.

[Purpose/significance]By constructing and applying the multi-dimensional portrait system of green technology innovation enterprises in China, this paper aims to comprehensively understand the status quo, advantages and obstacles of enterprises in specific fields in green technology innovation, so as to provide scientific references and suggestions for relevant government departments and decision makers of enterprises. [Method/process]Based on resource-based view and environmental dependence theory, we select the internal and external labels of enterprises, and designs a multi-dimensional label system to objectively describe the performance of enterprises in terms of profitability, scientific research and innovation, public opinion and environmental responsibility. Then, the green technology innovation efficiency index system is constructed from the input-output stage. The undirected super-efficiency SBM model is used to calculate the green technology innovation efficiency value of enterprises in each year, and the dynamic change trend of enterprise efficiency value is analyzed by Malmquist index. [Result/conclusion]This paper takes the field of green transportation as an example, verifies that the proposed method can effectively evaluate the green technology innovation ability of listed enterprises, and analyzes the reasons for the change of technical efficiency. In addition, through the clustering of financial strength, green innovation ability and social public opinion, five types of green transportation enterprises are obtained, which provides effective guidance for different types of enterprises to formulate differentiated competitive strategies.

[Purpose/significance]This study aims to automatically generate claims using the GPT-4 model, in order to reduce the writing difficulty for inventor and improve the work efficiency and quality. [Method/process]The article constructs Prompts suitable for automatically generating patent claims and implements four prompting strategies: Zero-Shot, Exact-Drafting, Stepwise-Claim, and Exact-Step Claim. By inputting patent specifications and technical disclosure documents into the GPT-4 model and using Prompts to guide its output, the automated generation of patent claims is achieved. The ROUGE and BERTScore evaluation metrics were used to assess the quality of the text, and the generated text was analyzed in comparison with the reference text from multiple dimensions, including the number of claims, text length, high-frequency words, keywords, and common collocations. Finally, the quality of the generated claim documents was evaluated through expert assessment in five aspects: clarity, consistency, relevance, professionalism, and completeness. [Result/conclusion]Empirical research shows that the Exact-Step Claim prompting strategy significantly improves the quality of generated claims; moreover, claims generated based on patent specifications are more closely matched in the number of claims and text length with the reference texts, indicating that the application effect of the GPT-4 model in the field of natural language understanding and generation is closely related to the quality of the input text. This study provides an efficient and intelligent assistance method that contributes to the development of the patent text writing and review field. However, there are challenges, and further improvements are needed for the model to precisely understand complex technical terms and comply with patent regulations, as well as to explore how to optimize the model's ability to judge the number of claims and the length of the text.

[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.

[Purpose/significance]This study aims to explore the influencing mechanisms of information addiction behavior among college students, providing valuable reference for the prevention and management of information addiction behavior among college students. [Method/process]The Stimulus-Organism-Response (S-O-R) theory is introduced, and the external stimuli in the process of college students' information addiction are summarized through literature review. The cognitive psychology that arises in the addiction process of the body is deeply analyzed, and the theoretical model of college students' information addiction behavior is constructed. The trigger path of college students' information addiction is empirically analyzed using structural equation modeling. [Result/conclusion]Based on the research results, information overload, intermittent rewards, and behavioral management significantly positively affect college students' avoidance of uncertainty, leading to information addiction. At the same time, information overload also makes college students produce information anxiety, and information anxiety significantly positively affects college students' information addiction behavior. targeted suggestions and countermeasures are proposed for higher education institutions, college student groups, and technology enterprises, which are conducive to improving the management system of higher education institutions, promoting students' adaptation to the information environment, and driving the better development couse of education.

[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/signficance]As an important tool for labor market observation， the relative robustness and other characteristics inherent in the traditional occupational classification system make it difficult to reflect changes in industrial talent demand in a timely manner. To solve this problem， this paper focuses on how to use digital means to map the relationship between occupations and skill requirements， and how to construct a multi-layer vocation-skill network and how to realize it. [Method/process]Firstly， design a set of cross-job descriptors， a common language for describing different jobs in Chinese context， in order to establish a vocation description framework for recruitment data development and utilization. Secondly， the Key technology of occupational intelligence classification based on job description text is established， and then a set of methods and models for the construction of a multi-layer vocational-skill network reflecting the gradual specialization of skill requirements are formed; Finally， the method is validated by taking Shanghai IC industry as an example. [Result/conclusion]The experimental results show that the multi-layered job-skill network， which originates from the actual employment activities of enterprises， can assist us in observing diverse industrial talent needs with multi-dimensional granularity and flexibility.

[Purpose/significance]The innovation of national defense-related science and technology promoting the development of new-quality fighting capacity has become a national strategic demand, effectively forecasting innovation pathways in national defense-related science and technology is of great significance to improve the innovation capability of national defense-related science and technology and create the Chinese new quality fighting capacity. [Method/process] In view of characteristics of the innovation of national defense-related science and technology, i.e. mutability, uncertainty and high risk, this thesis constructs a logical framework of forecasting innovation pathway in national defense-related science and technology based on the theoretical analysis of the core elements of forecasting innovation path, and adopts three submodels i.e. identification of military needs, prediction of key technologies and mining of supportive policies to forecast innovation pathway in national defense-related science and technology. [Result/conclusion]The research results show that the foundation model can effectively predict the development trend of national defense-related science and technology and key technological break throughs, which provide scientific basis for the decision-making of innovation of national defense-related science and technology and effectively promote the integration of the new quality productivity and the new quality fighting capacity.

[Purpose/significance]Regarding the responses to public emergencies published by official agencies on social media, this study aims to measure information transparency and empathy in the response text, and further to investigate their influence on public acceptance of responses. [Method/process]This study used public emergency responses published on Sina Weibo, a Chinese popular social media, as data source. Through carefully collecting and filtering, we finally acquired 170 public emergency responses released from 2021 to 2023. Furthermore, by using methods of content analysis, manual coding, and natural language processing, we measured information transparency of responses from three aspects: information disclosure, information accuracy, and information clarity; Meanwhile, we measured empathy in a response based on its used positive and negative emotional words and affective words. Moreover, the influence of information transparency and empathy of responses on public acceptance was investigated by employing negative binomial regression analysis method. [Result/conclusion]The results show that increasing transparency of responses generally significantly affects public acceptance. However, the strength and direction of the effect varies depending on the content of the specific response information and the linguistic expressions. In addition, excessively expressing empathy in responses negatively affects public acceptance. The findings of this study help enriching theoretical research results in the field of public emergency and crisis communication management, and provide a reference for official agencies to determine the content of a public emergency response and its linguistic expressions.

[Purpose/significance]To clarify the professional skill demand and change trend of high-tech enterprises from the perspective of supply and demand optimization is helpful to accelerate the aggregation of innovation elements, gradually establish technical groups and establish a sound cooperation system. [Method/process]Based on the resume information of incumbents in the Integrated Circuit（IC）field, the collaborative filtering recommendation algorithm in  the  ime dimension was used to predict and evaluate the relationship between enterprises and professional skills in the field. By combining Word2vec word vector model and LDA model, data mining and corpus expansion of resume information are carried out to identify skill topics. Then describe the evolution path of skill theme and carry out visual expression to clarify the development status and evolution law of skill theme in IC field. [Result/conclusion]The research shows that the collaborative filtering idea based on time dimension is suitable for the prediction of the relationship between enterprises and skills, with an average accuracy of 96.68%. The evolution of skill theme in IC field shows the trend of "aggregation→dispersion→reaggregation", and the evolution law of each skill theme path is different, which is embodied in spiral cross evolution, innovation iterative evolution and technology dependency evolution. The overall skill development trend and path change law of IC industry given by the study can provide more accurate retrieval methods and skill selection directions for high-tech enterprises and incumbents.

[Purpose/significance]Research methods in information science are one of the critical research directions in this field. Constructing a fine-grained research method corpus and extracting research method entities can help scholars quickly understand the research methods in this field, explore the evolution of methods and their future development trends, and lay the foundation for the service and application of the research method corpus in the subsequent digital wave. [Method/process]Firstly, based on academic articles published in the Journal of the China Society for Scientific and Technical Information from 2000 to 2023, this study randomly selected 50 articles and manually annotated the research methodology entities within them, using these as the training corpus for entity extraction. Secondly, two models, BERT-base-chinese and Chinese-BERT-wwm-ext, were selected for entity extraction, and the model with superior performance was chosen as the final entity extraction model for this study. [Result/conclusion]This paper constructs a fine-grained research method annotation corpus of informatics that includes six types of entities: theoretical entity, method entity, dataset entity, indicator entity, tool entity, and other entities. In the task of training an entity extraction model based on manually annotated corpora, the Chinese-BERT-wwm-ext model performed better, with an accuracy rate, recall rate, and F1 score of 0.808 2, 0.846 7, and 0.827 0, respectively. Furthermore, this paper conducts an analysis of the research method entities and their categories, discovering that research methodologies in information science are becoming increasingly diverse, with emerging technologies coexisting alongside traditional methods, each showcasing their unique strengths.

[Purpose/significance]The quantitative evaluation of existing effective artificial intelligence (AI) policies aims to provide reference for government department to formulate scientific and reasonable AI policies and promote the development of AI. [Method/process]Taking 10 AI policies in the Yangtze River Delta region from 2015 to 2024 as the research samples, the text mining method is used to construct the evaluation index system of AI policies in the Yangtze River Delta region, and conduct quantitative evaluation by combining the PMC index model. [Result/conclusion]The study found that from a macro policy text perspective, the average PMC index of the 10 AI policy samples in the Yangtze River Delta region was 7.11, indicating that the overall policy design was scientifically rational. From a micro policy text perspective, there were significant differences in the levels of AI policy texts in the Yangtze River Delta region. Based on the research conclusions, targeted policy improvement suggestions are proposed in terms of expanding the scope of policy targets, establishing a policy evaluation system, adjusting policy directions, and implementing policies tailored to local conditions.

[Purpose/significance]There are many relationships between method entities and application scenarios, problems, organizations and other entities. Extracting these entity relationships helps to capture the development trend of technology and promote the improvement of innovation ability. [Method/process]This paper discusses a method for extracting method entities and relations based on automatically generated syntactic templates. By designing a new adaptive template, the method improves flexibility and adaptability, reducing dependence on large-scale labeled data. Using a small number of seed triples, the method iteratively generates syntactic templates and extracts method entities and relations for the CSDN artificial intelligence topic blog. It also improves the extraction quality using a filter model. [Result/conclusion]After 5 rounds of iterative extraction, the triplet extraction accuracy of the model reaches 55.2%, which is better than the existing general model. The results show that this method can effectively use the limited labeled data to extract method entities and their relationships in specific fields, and provide support for scientific and technological information analysis in academia and industry.