1245 The Mission and Positioning of Intelligence Studies Education in the New Era Hot! Su Xinning DOI: 10.3772/j.issn.1000-0135.2020.12.001 Intelligence studies education has made great achievements over more than half a century of development and has welcomed new development opportunities with the age of big data. How can these opportunities be grasped and how can the associated challenges be met? Starting from the mission of intelligence studies education in the new era, this study discusses the positioning of intelligence studies education in the future. The study also propounds seven missions of intelligence studies education: the cultivation of professionals of Detector, Scout, and Consultant, leaders of science and technology, intelligence talents in the field of national security, intelligence talents who can act as decision-making advisers, intelligence scientists with an acute “sense of smell” in all walks of life, talents of consultancy service who serve the people, and scholars who explore the theory, technology, and methods of intelligence studies. Further, four orientations of intelligence studies education in the future are identified: following national strategies, strengthening the teaching of intelligence technology, aiming at the international environment, and keeping up with the times. 2020 Vol. 39 (12): 1245-1252 [Abstract] ( 195 ) HTML (77 KB)  PDF (1083 KB)  ( 1023 )

1253 Research on Information Science Curricula Based on Curriculum Knowledge Extraction Hot! Shen Si, Zuo Mingcong, Wang Dongbo, Ji Youshu, Liu Liu, Xie Jing DOI: 10.3772/j.issn.1000-0135.2020.12.002 The reform of information science curricula has become a hot topic in recent years. Based on an acquired curriculum of foreign iSchools, an automatic extraction model for course names is constructed combining the deep learning model of Bi-LSTM and BERT; the best value of the F-measure of the BERT model reached 92.92%. The knowledge extraction of all course names was completed with the model, and a comprehensive and systematic iSchool curriculum knowledge system was constructed. On the basis of the extracted knowledge, this study systematically and deeply analyzed the course contents of iSchool from the perspective of hierarchy and region. Some practical suggestions are provided for the design of the corresponding courses of information science in China on the basis of the above analysis. 2020 Vol. 39 (12): 1253-1263 [Abstract] ( 250 ) HTML (101 KB)  PDF (2795 KB)  ( 654 )

1264 Intelligence Studies Education in the Era of Big Data: A Review and Outlook Hot! Liu Liu, Wang Dongbo, Shen Si, Xie Jing, Chen Yucheng DOI: 10.3772/j.issn.1000-0135.2020.12.003 Based on the development of intelligence studies education in the era of big data, this study provides a comprehensive review of the history of the development of intelligence studies education since its restoration in 1978. Focusing on the connotation discussions, talent cultivation, and curriculum setting of information science education, a complete review of the development process of intelligence studies education is provided, especially the new development wave of intelligence studies education in the era of big data. This article provides a more detailed reference for the in-depth understanding of the development of intelligence studies education. 2020 Vol. 39 (12): 1264-1271 [Abstract] ( 235 ) HTML (131 KB)  PDF (1072 KB)  ( 754 )

1272 Analysis of the Current Situation of Intelligence Studies Teaching and Talent Cultivation in China Hot! Xie Jing, Wang Dongbo, Liu Liu, Shen Si DOI: 10.3772/j.issn.1000-0135.2020.12.004 This study reviews the development of intelligence studies education in China through a literature review. We also collect information about academic institutions of intelligence studies and details of their recruitment situations, professional curriculum, and talent training plans through a network investigation. The investigation shows that the education development of Chinese intelligence studies has made a great contribution to scientific and technological advances. Finally, we assert that intelligence studies education should focus on intelligence theory and technology to meet the demands of national security, social economics, and scientific and technologic advances in the new era of big data. 2020 Vol. 39 (12): 1272-1282 [Abstract] ( 306 ) HTML (129 KB)  PDF (1121 KB)  ( 1085 )

1283 Systems Intelligence and Organizational Intelligence: From Scenario-Based to Model-Based Intelligence Hot! Zhao Zhiyun, Sun Xingkai, Wang Xiao, Gao Fang, Wang Feiyue DOI: 10.3772/j.issn.1000-0135.2020.12.005 The Communist Party of China has unveiled in full the Party leadership’s proposals for formulating the 14th Five-Year Plan (2021-2025) for National Economic and Social Development and the Long-Range Objectives through the year 2035. The document highlights China’s new development stage, philosophy, and pattern. It insists on emphasizing the core position of innovation in the overall situation of China’s modernization drive, and on scientific and technological self-reliance as strategic support for national development. At the same time, it puts forward the system concept among the five principles for the first time. In the context of “innovative development, intelligence first”, we must reposition intelligence theory and methods in accordance with the new development concept in a new historical position. Considering the need for the development of information theory and practice under the guidance of the spirit of the Fifth Plenary Session of the 19th Central Committee, this paper puts forward the concepts and theories of organizational intelligence and systems intelligence, and explores the information service methods that adapt to the new development stage. Intelligence is the integration of Knowledge, Action, and Organization (KAO). Artificial intelligence provides more effective means for realizing the original intention of the KAO integration. However, the actual implementation of the KAO integration must rely on new concepts and methods of systems engineering, especially model-based systems engineering methods, using model-based intelligence, from organizational intelligence to systems intelligence, and from organizational smartness to system smartness, to build smart intelligence systems engineering. Focusing on this concept, raising corresponding questions and addressing key concerns of the Fifth Plenary Session are the essence of this article. 2020 Vol. 39 (12): 1283-1294 [Abstract] ( 247 ) HTML (109 KB)  PDF (1439 KB)  ( 913 )

1295 Research on Intelligent Services for Industrial Competitive Intelligence Driven by Multi-Source Data Hot! Zheng Rong, Yang Jingxiong, Zhang Wei, Chang Zeyu DOI: 10.3772/j.issn.1000-0135.2020.12.006 The competitive intelligence service industry will evolve and become more intelligent with time. As the basis of competitive intelligence, the use of multi-source data significantly impacts the realization of intelligent services for industrial competitive intelligence. This paper explores this issue in order to provide additional references for research on industrial competitive intelligence services. First, this paper analyzes the connotations and demand of smart services for multi-source data-driven industry competitive intelligence. Second, it clarifies the realization path of multi-source data-driven smart services for industrial competitive intelligence. According to the implementation plan, after the establishment of a multi-source data fusion framework comprising bottom-level fusion and middle-level and high-level integration, this paper expounds the role of industrial competitive intelligence services in different dimensions, focusing on four service modes—intelligent retrieval, personalized recommendation, special customization, and intelligent prediction. Multi-source data and its fusion is an important driving force for the intelligent transformation of industrial competitive intelligence services. A multi-source data-driven intelligent service for industrial competitive intelligence should use the demand for industrial intelligence as a reference point, take the multi-source data and its integration as the breakthrough point, and promote the realization of a multi-dimensional intelligent service for industrial competitive intelligence. 2020 Vol. 39 (12): 1295-1304 [Abstract] ( 208 ) HTML (78 KB)  PDF (3009 KB)  ( 916 )

1305 Research Review and Integrated Framework Construction for Environmental Scanning: An Exploration Based on Grounded Theory Hot! Shen Tao DOI: 10.3772/j.issn.1000-0135.2020.12.007 As an interdisciplinary research field, environmental scanning has attracted the attention of many academic schools and provides diversified research perspectives and contents. To address the lack of systematic combing or integration frameworks in environmental scanning research, based on the grounded theory method, this study encoded the research content of relevant literature to obtain 154 primary codes and 17 focused codes, from which six research themes were extracted: environmental context, organizational characteristics, personal characteristics, environmental scanning, organizational capability, and organizational output. Based on a systematic review of the relationship between research themes, a theoretical analysis framework of “antecedent-process-mechanism-output” (A-P-M-O) is constructed. Finally, combined with the theoretical and practical problems of organizational environment scanning in China, agendas that should be given attention in the future are identified with the hope of providing theoretical reference for further research and environmental scanning practices. 2020 Vol. 39 (12): 1305-1319 [Abstract] ( 229 ) HTML (175 KB)  PDF (1841 KB)  ( 630 )

1320 Recognition of Lexical Functions in Academic Texts: Automatic Classification of Keywords Based on BERT Vectorization Hot! Lu Wei, Li Pengcheng, Zhang Guobiao, Cheng Qikai DOI: 10.3772/j.issn.1000-0135.2020.12.008 As vocabulary or terminology that maps the full-text subject matter content in academic texts, keywords can provide important underlying semantic labels for knowledge retrieval and large-scale text computation. At present, there are problems in the use of keywords in academic texts, such as unclear intention, fuzzy semantic function, and lack of context information. Therefore, a neural network method based on supervised learning is proposed to classify the semantic functions carried by keywords to facilitate the identification of research questions and research methods in academic texts. In this study, journal papers published during a period of 10 years in the field of computer science were used as the training corpus, and the classification model was constructed using BERT and LSTM models. The results show that the proposed method is better than the traditional method. Its overall accuracy, recall rate, and F1 value reached 0.83, 0.87, and 0.85. 2020 Vol. 39 (12): 1320-1329 [Abstract] ( 175 ) HTML (101 KB)  PDF (2619 KB)  ( 1131 )

1330 An Empirical Study on Panoramic Data Portrait of Smart City from the Perspective of Digital Space Hot! Zhang Yanfeng, Zou Kai, Peng Lihui, Cao Dan DOI: 10.3772/j.issn.1000-0135.2020.12.009 From the perspective of digital space, this study analyzes the panoramic data portrait of a smart city, to present the trend of urban development in our country, realize the capacity of smart city construction at the data level, and then use the panoramic data portrait to assist the construction of a smart city. According to the inherent logical data of each dimension, a smart city data label framework is constructed. The grey-weighted correlation analysis method is used to evaluate, rank, and analyze the urban data to discover each dimension??s internal logic and external correlation. Four groups of data portrait group structure of smart city with significant differences are obtained by the K-means clustering analysis method. The data portrait??s key characteristics of each city type are analyzed concretely, which provide s a more comprehensive interpretation of data portrait label type for a smart city and realizes the panoramic data presentation of city operation status. 2020 Vol. 39 (12): 1330-1339 [Abstract] ( 178 ) HTML (154 KB)  PDF (1917 KB)  ( 730 )

1340 Communication of Scientific and Technological Innovation Information on Twitter: Analyzing Tweeting Behavior from the Perspective of Information Interaction Hot! Zhu Na, Wang Fang DOI: 10.3772/j.issn.1000-0135.2020.12.010 In recent years, the dissemination of scientific and technological innovation information on Twitter has become a hot topic of discussion in the field of Library and Information Science. Exploring the communication channels used by different users to discuss scientific and technological innovation through network scientific thinking can help identify the role of users in the communication process and reveal the characteristics of users’ communication behavior. Based on real communication data of Twitter users, this research encoded the types of users identified through content analysis, and divided them into seven types. Representing users as nodes, we visualized and analyzed the communication network in the subject area of scientific and technological innovation. By calculating the network structure parameters, we identified the communication behavior characteristics of different types of users and their communication roles. The results showed that, scientific researchers were the main actors in the dissemination of information about scientific and technological innovation, and journals and magazines had the highest degree of participation in communication. The direction of communication regarding scientific and technological innovation was from the scientific community to the public, from authoritative users to ordinary users. In the communication network, the information sources were either extremely rich or extremely poor; the capacity of information interaction between different types of users was poor. We found that blindly increasing the number of information sources could easily increase the opportunity cost of communication. Instead, we recommend appropriately increasing the number of high-quality information sources that are genuine and well-respected. In addition, enhancing the information interaction ability of the sources in the network community can also improve the scope of dissemination and popularization of scientific and technological innovation information. 2020 Vol. 39 (12): 1340-1353 [Abstract] ( 193 ) HTML (146 KB)  PDF (6247 KB)  ( 642 )

1354 Review of Research Progress on Low-citation of Scientific and Technical Literature Hot! Hu Zewen, Cui Jingjing, Cao Ling DOI: 10.3772/j.issn.1000-0135.2020.12.011 High-citation and low-citation of papers are both opposite and unified, universal phenomena in the science world. Although high-citation, due to its powerful positive guiding role, has received extensive attention from domestic and overseas scholars, we should not neglect the negative caution role of low-citation on scientific research’s quality and influence. In this study, we firstly clarified the background, related definitions, and significance of low-citation studies. Through comprehensively reading and analyzing all the related research literature on low-citation, we summarized four important research topics. They are the measurement of low-citation threshold and the percentages of lowly cited literature, time-changed patterns of low-citation rate, the determinants leading to low-citation and the prediction of the future value of lowly cited publications, and the application of the evaluation indicators related to low-citation. Finally, we further reviewed and commented on the development status and existing problems in the four above-mentioned important topics and proposed the future research plans and solutions for solving such problems. Our purpose is to provide a general picture of low-citation for readers who are interested in this topic. 2020 Vol. 39 (12): 1354-1362 [Abstract] ( 211 ) HTML (121 KB)  PDF (1168 KB)  ( 794 )