Search (36 results, page 1 of 2)

  • × author_ss:"Zhang, J."
  1. Geng, Q.; Townley, C.; Huang, K.; Zhang, J.: Comparative knowledge management : a pilot study of Chinese and American universities (2005) 0.01 
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  2. Zhang, J.; An, L.; Tang, T.; Hong, Y.: Visual health subject directory analysis based on users' traversal activities (2009) 0.01 
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    Abstract
    Concerns about health issues cover a wide spectrum. Consumer health information, which has become more available on the Internet, plays an extremely important role in addressing these concerns. A subject directory as an information organization and browsing mechanism is widely used in consumer health-related Websites. In this study we employed the information visualization technique Self-Organizing Map (SOM) in combination with a new U-matrix algorithm to analyze health subject clusters through a Web transaction log. An experimental study was conducted to test the proposed methods. The findings show that the clusters identified from the same cells based on path-length-1 outperformed both the clusters from the adjacent cells based on path-length-1 and the clusters from the same cells based on path-length-2 in the visual SOM display. The U-matrix method successfully distinguished the irrelevant subjects situated in the adjacent cells with different colors in the SOM display. The findings of this study lead to a better understanding of the health-related subject relationship from the users' traversal perspective.
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  3. Gao, J.; Zhang, J.: Clustered SVD strategies in latent semantic indexing (2005) 0.01 
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    Language
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    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  4. Zhang, J.; Wolfram, D.; Wang, P.; Hong, Y.; Gillis, R.: Visualization of health-subject analysis based on query term co-occurrences (2008) 0.01 
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    Abstract
    A multidimensional-scaling approach is used to analyze frequently used medical-topic terms in queries submitted to a Web-based consumer health information system. Based on a year-long transaction log file, five medical focus keywords (stomach, hip, stroke, depression, and cholesterol) and their co-occurring query terms are analyzed. An overlap-coefficient similarity measure and a conversion measure are used to calculate the proximity of terms to one another based on their co-occurrences in queries. The impact of the dimensionality of the visual configuration, the cutoff point of term co-occurrence for inclusion in the analysis, and the Minkowski metric power k on the stress value are discussed. A visual clustering of groups of terms based on the proximity within each focus-keyword group is also conducted. Term distributions within each visual configuration are characterized and are compared with formal medical vocabulary. This investigation reveals that there are significant differences between consumer health query-term usage and more formal medical terminology used by medical professionals when describing the same medical subject. Future directions are discussed.
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  5. Zhang, L.; Liu, Q.L.; Zhang, J.; Wang, H.F.; Pan, Y.; Yu, Y.: Semplore: an IR approach to scalable hybrid query of Semantic Web data (2007) 0.01 
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    Source
    Proceeding ISWC'07/ASWC'07 : Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference. Ed.: K. Aberer et al
  6. An, L.; Zhang, J.; Yu, C.: ¬The visual subject analysis of library and information science journals with self-organizing map (2011) 0.01 
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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.
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  7. Zhang, J.; Mostafa, J.; Tripathy, H.: Information retrieval by semantic analysis and visualization of the concept space of D-Lib® magazine (2002) 0.00 
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    Language
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    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  8. 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
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  9. Zhang, J.: TOFIR: A tool of facilitating information retrieval : introduce a visual retrieval model (2001) 0.00 
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  10. Patrick, J.; Zhang, J.; Artola-Zubillaga, X.: ¬An architecture and query language for a federation of heterogeneous dictionary databases (2000) 0.00 
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  11. Zhang, J.; Dimitroff, A.: Internet search engines' response to Metadata Dublin Core implementation (2005) 0.00 
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  12. Zhuge, H.; Zhang, J.: Topological centrality and its e-Science applications (2010) 0.00 
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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.
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  13. Hansen, D.L.; Khopkar, T.; Zhang, J.: Recommender systems and expert locators (2009) 0.00 
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    Footnote
    Vgl.: http://www.tandfonline.com/doi/book/10.1081/E-ELIS3.
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  14. Zhang, J.: ¬A representational analysis of relational information displays (1996) 0.00 
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  15. Zhang, J.; Korfhage, R.R.: ¬A distance and angle similarity measure method (1999) 0.00 
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  16. Zhang, J.; Korfhage, R.R.: DARE: Distance and Angle Retrieval Environment : A tale of the two measures (1999) 0.00 
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  17. Zhang, J.; Dimitroff, A.: ¬The impact of webpage content characteristics on webpage visibility in search engine results : part I (2005) 0.00 
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  18. Zhang, J.; Jastram, I.: ¬A study of the metadata creation behavior of different user groups on the Internet (2006) 0.00 
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  19. Zhang, J.; Dimitroff, A.: ¬The impact of metadata implementation on webpage visibility in search engine results : part II (2005) 0.00 
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  20. Zhang, J.; Dimitroff, A.: ¬The impact of metadata implementation on webpage visibility in search engine results : part II (2005) 0.00 
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