Search (10 results, page 1 of 1)

  • × author_ss:"Zhang, J."
  • × language_ss:"e"
  • × year_i:[2010 TO 2020}
  1. Zhang, J.; Zhao, Y.: ¬A user term visualization analysis based on a social question and answer log (2013) 0.01 
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    Source
    Information processing and management. 49(2013) no.5, S.1019-1048
  2. Zhuge, H.; Zhang, J.: Topological centrality and its e-Science applications (2010) 0.01 
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    Abstract
    Network structure analysis plays an important role in characterizing complex systems. Different from previous network centrality measures, this article proposes the topological centrality measure reflecting the topological positions of nodes and edges as well as influence between nodes and edges in general network. Experiments on different networks show distinguished features of the topological centrality by comparing with the degree centrality, closeness centrality, betweenness centrality, information centrality, and PageRank. The topological centrality measure is then applied to discover communities and to construct the backbone network. Its characteristics and significance is further shown in e-Science applications.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.9, S.1824-1841
  3. Zhang, J.; Yu, Q.; Zheng, F.; Long, C.; Lu, Z.; Duan, Z.: Comparing keywords plus of WOS and author keywords : a case study of patient adherence research (2016) 0.00 
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    Abstract
    Bibliometric analysis based on literature in the Web of Science (WOS) has become an increasingly popular method for visualizing the structure of scientific fields. Keywords Plus and Author Keywords are commonly selected as units of analysis, despite the limited research evidence demonstrating the effectiveness of Keywords Plus. This study was conceived to evaluate the efficacy of Keywords Plus as a parameter for capturing the content and scientific concepts presented in articles. Using scientific papers about patient adherence that were retrieved from WOS, a comparative assessment of Keywords Plus and Author Keywords was performed at the scientific field level and the document level, respectively. Our search yielded more Keywords Plus terms than Author Keywords, and the Keywords Plus terms were more broadly descriptive. Keywords Plus is as effective as Author Keywords in terms of bibliometric analysis investigating the knowledge structure of scientific fields, but it is less comprehensive in representing an article's content.
    Object
    Web of Science
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.4, S.967-972
  4. Zhang, J.; Zeng, M.L.: ¬A new similarity measure for subject hierarchical structures (2014) 0.00 
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    Date
    8. 4.2015 16:22:13
  5. An, L.; Zhang, J.; Yu, C.: ¬The visual subject analysis of library and information science journals with self-organizing map (2011) 0.00 
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    Abstract
    Academic journals play an important role in scientific communication. The effective organization of journals can help reveal the thematic contents of journals and thus make them more user-friendly. In this study, the Self-Organizing Map (SOM) technique was employed to visually analyze the 60 library and information science-related journals published from 2006 to 2008. The U-matrix by Ultsch (2003) was applied to categorize the journals into 19 clusters according to their subjects. Four journals were recommended to supplement library collections although they were not indexed by SCI/SSCI. A novel SOM display named Attribute Accumulation Matrix (AA-matrix) was proposed, and the results from this method show that they correlate significantly with the total occurrences of the subjects in the investigated journals. The AA-matrix was employed to identify the 86 salient subjects, which could be manually classified into 7 meaningful groups. A method of the Salient Attribute Projection was constructed to label the attribute characteristics of different clusters. Finally, the subject characteristics of the journals with high impact factors (IFs) were also addressed. The findings of this study can lead to a better understanding of the subject structure and characteristics of library/information-related journals.
  6. Liu, X.; Zhang, J.; Guo, C.: Full-text citation analysis : a new method to enhance scholarly networks (2013) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.9, S.1852-1863
  7. Li, D.; Tang, J.; Ding, Y.; Shuai, X.; Chambers, T.; Sun, G.; Luo, Z.; Zhang, J.: Topic-level opinion influence model (TOIM) : an investigation using tencent microblogging (2015) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2657-2673
  8. Zhang, J.; Zhai, S.; Liu, H.; Stevenson, J.A.: Social network analysis on a topic-based navigation guidance system in a public health portal (2016) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.5, S.1068-1088
  9. Zhang, J.; Zhai, S.; Stevenson, J.A.; Xia, L.: Optimization of the subject directory in a government agriculture department web portal (2016) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.9, S.2166-2180
  10. Li, D.; Luo, Z.; Ding, Y.; Tang, J.; Sun, G.G.-Z.; Dai, X.; Du, J.; Zhang, J.; Kong, S.: User-level microblogging recommendation incorporating social influence (2017) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.3, S.553-568

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