1 Characteristics of Knowledge Diffusion in Disciplinary Citation Network Yue Zenghui, Xu Haiyun DOI: 10.3772/j.issn.1000-0135.2019.01.001 In the era of the knowledge-driven economy, the diffusion of disciplinary knowledge promotes disciplinary collaboration, integration, development, and innovation. In this paper, the diffusion characteristics of disciplinary knowledge are systematically studied by taking citations as the carrier of the transmission path, so as to explore the rules and patterns of disciplinary knowledge flow and provide a theoretical and empirical basis for the integration, transformation, and innovation of disciplinary knowledge. First, the quantitative measurement of the quantity features of knowledge diffusion is carried out by using 8 measurement indexes. Second, descriptive statistics are selected to describe the diffusion characteristics of disciplinary knowledge from the perspectives of centralization trend, dispersion degree, and distribution form. Third, the betweenness characteristics and the role of the intermediary in the diffusion of disciplinary knowledge are analyzed by applying the method of social network analysis. Finally, an empirical study is further conducted by taking the field of social networking as an example. The research has shown that knowledge exchanges among disciplines in the field of social networks are frequent, in which multidisciplinary sciences, sociology, information science, library science, etc. are active disciplines with strong information and control advantages. The characteristic indexes of disciplinary knowledge diffusion fluctuate in a wide range, with a high degree of dispersion. Information science and library science mainly play the role of liaison, which is an important medium for exchanging knowledge among various disciplines. 2019 Vol. 38 (1): 1-12 [Abstract] ( 257 ) HTML (162 KB)  PDF (1023 KB)  ( 916 )

13 Patent Screening of Core Documents and Impact of Patent Technology Subject Identification Li Shuying, Zhang Xin, Xu Yi, Xu Haiyu, Zhang Xian, Zhu Yuexian DOI: 10.3772/j.issn.1000-0135.2019.01.002 Technical feature words are considered to play a key role in technology networks. This study compares the efficiency of technical feature words extracted from the core patent dataset with those of the whole dataset and discusses the impact of core patent screening on the identification of technology features based on citation networks. This study applies the patent citation intensity indicator and citation time lag into patent screening of core patent documents in two steps. Furthermore, the differences between core documents and whole documents were identified in terms of word cloud, word frequency coverage, threshold selection, and division of technical topics. An empirical analysis on the biomedicine applications of graphene indicates that the feature words extracted from the core patent dataset help increase recognition efficiency and accuracy, and the technology co-classification network generated from the core dataset is more focused than the one generated from the whole network; this effectively simplifies data cleaning and also aids topic identification and expert interpretation. 2019 Vol. 38 (1): 13-20 [Abstract] ( 311 ) HTML (100 KB)  PDF (5756 KB)  ( 625 )

21 Development of Social Network Analysis (SNA) Using Intelligence Analysis Chen Yunwei DOI: 10.3772/j.issn.1000-0135.2019.01.003 The purpose of this paper was to conclude the development of social network analysis (SNA) using intelligence analysis through the following three aspects: collaboration network, citation network, and topic-associated network. This paper emphasizes combining classic concepts, methods, and algorithms, as well as introducing new concepts, ideas, indicators, and algorithms. Finally, this paper discusses the functions and prospects of SNA. 2019 Vol. 38 (1): 21-28 [Abstract] ( 606 ) HTML (132 KB)  PDF (656 KB)  ( 669 )

29 Collaborative Features of Authors Based on Academic Journal Papers and Their Influence on Scientific Research Output— Taking Highly Published Authors of International Medical Informatics as an Example Zhang Xue, Zhang Zhiqiang, Chen Xiujuan DOI: 10.3772/j.issn.1000-0135.2019.01.004 In order to realize the characteristics of collaboration and output in scientific research, propose improvements to research collaboration models, increase collaboration awareness, help scientific researchers choose better research partners, establish an efficient research collaboration network, improve academic research output, and promote scientific development. This study uses 200 high-yielding authors in the field of international medical informatics as an example to conduct a literature review, and social network, bibliometric, statistical analyses. First, a correlation analysis is carried out to investigate the relationships among measurement indicators of scientific research output, such as the number of articles, number of articles cited, h-index, and number of papers whose citation exceeds a certain eigenvalue n, and scientific research collaboration indicators such as point degree, intermediary center, structural hole, collaboration ability index, collaboration degree, collaboration rate, and collaboration coefficient. Then, the principal component analysis method is adopted to extract the common factors. Finally, using the newly constructed scientific research output measurement index as the dependent variable and the scientific research collaboration measurement index as the independent variable, a multivariate statistical analysis is undertaken. The results show that the phenomenon of scientific research collaboration in the field of medical informatics is increasingly common. Under different collaboration modes, there are differences in the distribution of scientific research output of scholars. The increase in the number of fixed collaborations between authors does not reflect the high degree of heterogeneity among the cooperating groups. If researchers want to improve scientific research output, they should focus on establishing a stable and high-frequency collaboration model with partners and strive to cooperate with researchers from different disciplines to improve partner diversity. 2019 Vol. 38 (1): 29-37 [Abstract] ( 409 ) HTML (132 KB)  PDF (740 KB)  ( 710 )

38 History and Development of Scientific and Technical Intelligence in China Liu Ru, Wu Chensheng, Liu Yanjun, Li Hui, Li Menghui DOI: 10.3772/j.issn.1000-0135.2019.01.005 The historical evolution and missions of China's scientific and technical intelligence are examined to provide reference for their future development. Through literature research, field visits and historical research methods, comprehensively review the history, development and status quo of China's scientific and technological intelligence institutions. This study aims to summarize the values, significance, and functional characteristics of scientific and technical intelligence work undertaken in China for the purpose of revealing their fundamental mission and cultural consciousness. This paper systematically summarizes the historical development, system reform, and work on scientific and technical intelligence, based on which, the country’s future prospects are indicated with the principle of respecting traditional values but also promoting innovation. 2019 Vol. 38 (1): 38-45 [Abstract] ( 339 ) HTML (92 KB)  PDF (1116 KB)  ( 970 )

46 Research on Theory Model and Running of the Decision-driven Intelligence Process Li Pin, Xu Linyu, Yang Jianlin DOI: 10.3772/j.issn.1000-0135.2019.01.006 Supporting decision-making is an important function of intelligence studies, and scientific and reasonable intelligence process is required as a guarantee for realizing this function. In order to ensure that intelligence work can produce high-quality intelligence products, and can be accepted by decision makers, and can affect the decision-making process of decision makers, this paper proposes a decision-driven intelligence process model. The model emphasizes the decision-making needs in the context of subjective and objective interweaving, the follow-up of intelligence activities in their changes and the feedback of multiple and repeated cycles, realizes the deep-seated dialogue between decision makers and information work, advocates the free flow of resources, and emphasizes the formation of networks between intelligence collectors and analysts so as to ensure the sufficiency of decision makers and intelligence workers. The interaction will drive the continuous operation of the intelligence process. The model provides an action guide for intelligence work supporting decision-making, provides a basis for intelligence management oriented to intelligence practice, provides guidance for training comprehensive practical ability of intelligence talents, and provides a new growth point for theoretical innovation oriented to interdisciplinary science. 2019 Vol. 38 (1): 46-57 [Abstract] ( 393 ) HTML (153 KB)  PDF (1072 KB)  ( 880 )

58 Theoretical Thinking on City Profile from the Perspective of Digital Space Ma Yaxue, Li Gang, Xie Hui, Ma Chao DOI: 10.3772/j.issn.1000-0135.2019.01.007 The construction of smart cities can effectively improve the capability of urban governance and operation and break the dilemma of modern urban development. In this paper, we aim to explore how to use big data in urban physical, social, and cyber spaces to construct smart cities. Relying on the three-world theory to analyze the composition of urban space, the concept of urban digital space was proposed to help achieve the construction of smart cities, and city profiling was accordingly presented as a construction method of urban digital spaces and city profiles. According to the goal of constructing urban digital space, we first analyzed the concept of the city profile. Then, we illustrated how to realize the construction of city profiles through urban facet modeling and profiling with smart data. Finally, we discussed the feasible applicable fields of city profiles and analyzed three typical application scenarios in detail. The urban digital space constructed by city profiling can provide a panoramic view of the urban operating conditions, treating cities as organisms that are assisted by smart data to govern, operate, and develop, and then intelligent information services can be provided to users. 2019 Vol. 38 (1): 58-67 [Abstract] ( 210 ) HTML (105 KB)  PDF (3244 KB)  ( 1032 )

68 Research on Chinese Named Entity Linking Based on Multi-feature Fusion Lin Zefei, Ou Shiyan DOI: 10.3772/j.issn.1000-0135.2019.01.008 Named Entity Linking (NEL) refers to a named entity disambiguation method that disambiguates multi-sense named entity mentions in a text by mapping them to their correct meanings in a knowledge base. Most of the current NEL studies and practices focus on named entity disambiguation in western texts, rather than Chinese texts, by using Wikipedia. However, this study proposed a Chinese named entity linking method based on the Baidu Encyclopedia. This method integrates single and collective named entity disambiguation features, and adopts different combinations of features in accordance with the different text lengths. In addition, a two-stage disambiguation strategy, which can optimize the result of the first-round of disambiguation, was designed. The results of this experiment on real Chinese corpora showed that disambiguation accuracy can be significantly improved by multi-feature fusion and two-stage disambiguation. A comparative experiment demonstrated that the performance of this NEL method is superior to that of a similar state-of-the-art system (the Chinese NEL service of Knowledge Works Lab at Fudan University). 2019 Vol. 38 (1): 68-78 [Abstract] ( 217 ) HTML (142 KB)  PDF (2457 KB)  ( 853 )

79 Research on Abstract Structure Function Automatic Recognition Based on Full Character Semantics Shen Si, Hu Haotian, Ye Wenhao, Wang Dongbo DOI: 10.3772/j.issn.1000-0135.2019.01.009 The structure of each academic-literature abstract has a specific function. However, there are relatively few studies on the automatic recognition of the structural abilities of academic abstracts at present; furthermore, these studies have some problems, such as methods that are too traditional, as well as insignificant recognition. Based on the deep learning method of the LSTM-CRF model with sequence properties, this paper constructed an automatic structure recognition model that uses the semantic information contained in all characters in the abstract, and compared the result with SVM models without sequence properties, RNN, CRF and LSTM with sequence properties in multiple angles by taking the character as the basic semantic unit. The model proposed in this paper achieved remarkable results in accuracy, recall, and F-value in structure recognition, with the highest F-value reaching 85.47%. Compared with the models of RNN, LSTM, CRF, and SVM, its performance is enhanced by 33.63%, 32.81%, 39.13%, and 38.33%, respectively. 2019 Vol. 38 (1): 79-88 [Abstract] ( 240 ) HTML (140 KB)  PDF (2129 KB)  ( 768 )

89 Research on Microblog Rumor Identification Based on LDA and Random Forest Zeng Ziming, Wang Jing DOI: 10.3772/j.issn.1000-0135.2019.01.010 The spread of Internet rumors has a negative impact on everyday life and social stability. In order to assist in rumor control, this paper analyzes information about the “haze” rumors on the Sina Weibo microblogging platform in 2016, and constructs reliability and influence variables based on Weibo data and history research. In addition, the LDA model is used to gather the topic distribution of the experimental text data. Based upon the reliability variable, the influence variable, and the probability of topics, the paper uses random forest for classification to achieve rumor identification. The experiment results show that the probability of topics plays an important role in rumor identification, and that the random forest model, based on LDA, can lead to an improvement in the accuracy of rumor identification. 2019 Vol. 38 (1): 89-96 [Abstract] ( 302 ) HTML (106 KB)  PDF (1147 KB)  ( 1018 )

97 Review of Internatinonal Studies on Discovering Emerging Topics Lu Chao, Hou Haiyan, Ding Ying, Zhang Chengzhi DOI: 10.3772/j.issn.1000-0135.2019.01.011 The detection of emerging topics is a research area that has been increasingly attracting numerous scholars' attention. An extensive knowledge of the dynamics of emerging topics in science and technology not only provides our government with support to make decisions on policies regarding guidelines for scientific research in order to improve profits from financial investments on scientific research and to accelerate the development of science, but can also offer scientific professionals directions for promising research areas that can help them dedicate themselves to scientific discovery. Although we used summaries of relevant literature on this topic that were published in international core journals, we found no clear definition for “emerging topic” or its related terms. The resulting methodology, therefore, has some limitations to conquer. Indicators for identifying emerging topics vary across the literature. Based on our investigation on the studies in this area, we proposed a definition for “emerging topic” and identified its attributes. Moreover, we also compared “emerging topic” with its related terms and identified some areas worth noting when detecting emerging topics in scientific research. Finally, we presented four aspects of this topic that require further study in the future. 2019 Vol. 38 (1): 97-110 [Abstract] ( 214 ) HTML (236 KB)  PDF (994 KB)  ( 1097 )