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Zhang, J.; Zeng, M.L.: ¬A new similarity measure for subject hierarchical structures (2014)
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- 8. 4.2015 16:22:13
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Zhang, J.; Korfhage, R.R.: ¬A distance and angle similarity measure method (1999)
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Zhang, J.; Korfhage, R.R.: DARE: Distance and Angle Retrieval Environment : A tale of the two measures (1999)
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Zhang, J.; Nguyen, T.: WebStar: a visualization model for hyperlink structures (2005)
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- 27.12.2007 12:03:07
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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)
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- 19. 3.2016 12:25:39
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Zhang, J.; Wolfram, D.; Wang, P.; Hong, Y.; Gillis, R.: Visualization of health-subject analysis based on query term co-occurrences (2008)
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- Source
- Journal of the American Society for Information Science and Technology. 59(2008) no.12, S.1933-1947
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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)
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- Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2657-2673
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Zhang, J.; Zhao, Y.: ¬A user term visualization analysis based on a social question and answer log (2013)
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- Abstract
- The authors of this paper investigate terms of consumers' diabetes based on a log from the Yahoo!Answers social question and answers (Q&A) forum, ascertain characteristics and relationships among terms related to diabetes from the consumers' perspective, and reveal users' diabetes information seeking patterns. In this study, the log analysis method, data coding method, and visualization multiple-dimensional scaling analysis method were used for analysis. The visual analyses were conducted at two levels: terms analysis within a category and category analysis among the categories in the schema. The findings show that the average number of words per question was 128.63, the average number of sentences per question was 8.23, the average number of words per response was 254.83, and the average number of sentences per response was 16.01. There were 12 categories (Cause & Pathophysiology, Sign & Symptom, Diagnosis & Test, Organ & Body Part, Complication & Related Disease, Medication, Treatment, Education & Info Resource, Affect, Social & Culture, Lifestyle, and Nutrient) in the diabetes related schema which emerged from the data coding analysis. The analyses at the two levels show that terms and categories were clustered and patterns were revealed. Future research directions are also included.
