1077 Research on Semantic Annotation in Academic Literature Sun Jianjun, Pei Lei, Jiang Ting DOI: 10.3772/j.issn.1000-0135.2018.11.001 Since the vast size of academic literature can present difficulties to researchers, semantic annotation is essential to rapid reading and knowledge acquisition. In order to regulate and enrich the semantic annotation system of academic literature, this paper focuses on the construction of an annotation ontology, the construction of a domain ontology of discipline domains, and the relationship between the terms in annotation ontology and domain ontology. This paper provides several instances of semantic annotation, such as labeling concepts, relationship of concepts, methods, processes and citations in academic literatures. 2018 Vol. 37 (11): 1077-1086 [Abstract] ( 240 ) HTML (1 KB)  PDF (1351 KB)  ( 726 )

1087 Technological Path Detection Approach Based on Association Analysis Wan Xiaoping, Liu Xiang, Yan Xiaoting, Wang Jinxia DOI: 10.3772/j.issn.1000-0135.2018.11.002 Discovering the technological path is of great significance in tracing the history of technology development, predicting technology development trends, and learning advanced technologies. We design a dynamic support threshold to filter unnecessary patents and then form a patented technology network based on the relationship between patent citations. Finally, we obtain a simplified technological path map with the path searching algorithm. Compared to the main path analysis method, our proposed method is more reasonable and accurate in selecting key patent nodes and analyzing patent relations. We test and verify the effectiveness and advantages of our method by applying it to the field of organic light-emitting diodes. 2018 Vol. 37 (11): 1087-1094 [Abstract] ( 346 ) HTML (1 KB)  PDF (549 KB)  ( 674 )

1095 A Method of Knowledge Evolution Analysis of ESI Research Fronts Based on Knowledge Element Co-occurrence Sun Zhen, Leng Fuhai DOI: 10.3772/j.issn.1000-0135.2018.11.003 This paper proposes a method for analyzing the knowledge evolution of ESI research fronts based on knowledge element co-occurrence. The method consists of text mining and natural language processing techniques to quantitatively monitor the characteristics of the knowledge flow of research fronts from a microscopic perspective, the findings of which can be used in strategic intelligence research. Based on the documents cited from the main papers comprising the 2016 Research Front report, the knowledge elements related to key innovations from each document were first extracted using the named entity recognition technology and then the centrality and modularity features of the knowledge elements’ co-occurrence networks were analyzed using time series analysis; this was done with the intention of presenting the law of knowledge evolution as it relates to research fronts from the perspective of structural change in scientific knowledge. Through a comparison of the results from the co-occurrence analysis based on keywords and terms, the advanced level and practical applicability of this method were demonstrated using the results of the 2017 Research Front report and authoritative conference papers. This study showed that this method can be used to reveal the microscopic development path and the varying patterns of the research fronts by reorganizing and analyzing the key elements of innovation in the papers. 2018 Vol. 37 (11): 1095-1113 [Abstract] ( 287 ) HTML (1 KB)  PDF (10047 KB)  ( 707 )

1114 Deep Learning-Based Classification of Pre-Qin Classics Questions Wang Dongbo, Gao Ruiqing, Shen Si, Li Bin DOI: 10.3772/j.issn.1000-0135.2018.11.004 In recent years, the automated question answering system has become a research hotspot in the fields of machine learning, information retrieval, and natural language processing. This question answering system provides simple and accurate answers in a natural language to the questions posed by users. Since question classification is the first step toward developing a question answering system, the classification results make a direct impact on the quality of a question answering system. However, most of the current question classification research in the field focuses on modern Chinese, and there are relatively few studies on the classification of the questions related to ancient Chinese. This paper starts with the concept of question classification and constructs the question classification system for ancient documents; and then uses TF-IDF to extract the category feature words. We use a support vector machine, conditional random fields, and a deep learning model, to conduct the classics question automatic classification experiment. The results show that the Bi-LSTM model offers the best classification among the three, and delivered a reconciliation average of 94.78 on the seven categories proposed in this paper, which has a strong application value. 2018 Vol. 37 (11): 1114-1122 [Abstract] ( 278 ) HTML (1 KB)  PDF (927 KB)  ( 706 )

1123 Research on the Relevance between Competitiveness and the Scientific Research Output of World-Class Universities Zhang Weichong, Meng Hao, Wang Fang DOI: 10.3772/j.issn.1000-0135.2018.11.005 Exploring the core elements characterizing the competitiveness of world-class universities and formulating the correct path to its improvement is of great significance for building a world-class university. This article examines the top 50 universities in the World University Rankings as samples. First, nine representative research output measurement indicators, X1-X9, were selected for statistical analysis, which included the four dimensions of productivity, influence, contribution, and level of internationalization. Second, X1-X9 were set as the independent variables and each university’s score in the QS/USNEWS/THE/ARWU university rankings was established as a dependent variable, Yi. The variable selection and parameter estimation experiments were carried out with four multiple linear regression models, Lasso/Ridge/LassoLars/BayesianRidge, and finally a well-fitting effect was obtained. The results reveal positive correlations between the impact factors of scientific research output, the total citation frequency, the number of cooperation organizations, and the annual average frequency of international cooperation with the competitiveness of world-class universities. However, results also showed that the number of papers per year, the growth rate of papers, the number of co-authors, the total annual frequency of institutional cooperation, and the frequency of cooperation between countries are not significantly related to the competitiveness of world-class universities. 2018 Vol. 37 (11): 1123-1131 [Abstract] ( 193 ) HTML (1 KB)  PDF (481 KB)  ( 806 )

1132 Applicability and Improvement of the z-index to Evaluate Academic Journals Yu Liping, Wang Zuogong DOI: 10.3772/j.issn.1000-0135.2018.11.006 The z-index is a composite bibliometric indicator that is evaluated based on quantity, quality, and consistency. An analysis of its characteristics and applicability to periodical evaluation is of great significance. Based on an analysis of the principles of the z-index and the CSSCI journals of Library and Information Sciences, this paper uses correlation coefficient and partial least square regression to analyze the characteristics of the z-index. It was found that the z-index is not suitable for the evaluation of an academic journal and cannot adequately reflect a perspective of quality and consistency, primarily because the concentration of works cited is too difficult to control. This paper proposed using the inverse of the low cited paper ratio instead of the cited concentration and named it the zn-index. Further research shows that the zn-index comprehensively enhances the z-index and has an improved effect on the evaluation. Moreover, the z-index should be selected carefully. Subsequently, the composite index of multiplication tends to have higher sensitivity. In conclusion, this paper provides a research paradigm for testing composite indexes. 2018 Vol. 37 (11): 1132-1139 [Abstract] ( 315 ) HTML (1 KB)  PDF (385 KB)  ( 569 )

1140 Study on Recognition Methods for Interdisciplinary Periodicals Zhang Huiling, Xu Haiyun, Liu Chunjiang DOI: 10.3772/j.issn.1000-0135.2018.11.007 In view of the utility of interdisciplinary journal identification methods, this paper systematically reviews the research on these methods both at home and abroad. Based on this, interdiscipline characteristics, the interdisciplinary recognition method is applied to interdisciplinary journal identification. Through interdisciplinary identification methods and comparative analysis of journal papers, the specific formula was amended by identifying and selecting the indicators with higher validity of interdisciplinary journal identification. The empirical results show that the indicators of interdisciplinary journal identification can be divided into academic periodical diversity indicators, balance indicators, aggregation indicators, and comprehensive indicators. The applicability of journal identification indicators varies in different disciplines. Among these indicators, the S-index for measuring periodical diversity, while the GI-index for focusing on journal balance have a good effect on cross-sectional measurement of journal subjects, and they can be used for interdisciplinary journal identification. 2018 Vol. 37 (11): 1140-1153 [Abstract] ( 183 ) HTML (1 KB)  PDF (537 KB)  ( 626 )

1154 Research on the Impact of Reputation Systems on Knowledge Sharing Activities in Social Q&A Community Shen Yufei, Liao Bo, Xu Yang DOI: 10.3772/j.issn.1000-0135.2018.11.008 Social question & answering communities (SQAC) have been more and more popular in recent years as a type of user repository. To incentivize users to share knowledge continuously, reputation systems are embedded. This paper aims at investigating whether the two major mechanisms of social influence, namely popularity influence and online word-of-mouth (WOM), exist in SQAC. Real-world data are collected from Zhihu, one of the most influential SQAC. We construct a panel dataset and specify dynamic panel models for econometric analysis. The empirical result from system GMM (generalized methods of moments) suggests that both mechanisms have positive impacts on the social endorsement of knowledge sharing. Theoretical contributions and managerial implications are also discussed. 2018 Vol. 37 (11): 1154-1163 [Abstract] ( 172 ) HTML (1 KB)  PDF (447 KB)  ( 917 )

1164 Information Searching Behavior of Digital Library Users Based on Their Cognitive Styles Zhang Lulu, Huang Kun DOI: 10.3772/j.issn.1000-0135.2018.11.009 To better understand the differences in searching behavior by digital library users exercising different cognitive styles, this research recruited 30 participants from the Beijing Normal University to take part in the experimental study. It detected the specific, generic, and abstract searching tasks, and recorded the participants’ searching process. Using content analysis, it analyzes the differences between field-independent users and field-dependent users, with respect to the overall characteristics, and particularly search behavior characteristics within a searching session. The findings indicated that the differences in the key searching behaviors between the two kinds of users were significant. This includes the use of search points and search function, the frequency of queries, the duration time within one searching session, and the patterns of query reformulations. 2018 Vol. 37 (11): 1164-1174 [Abstract] ( 356 ) HTML (1 KB)  PDF (498 KB)  ( 607 )