Journal of Shandong University(Engineering Science) ›› 2019, Vol. 49 ›› Issue (4): 29-35.doi: 10.6040/j.issn.1672-3961.0.2017.400

• Machine Learning & Data Mining • Previous Articles     Next Articles

Visualization of interactive ThemeRiver based on time-series data

Xindi CHEN(),Tianrui LI*(),Huanhuan YANG   

  1. School of Information Science and Technology, Southwest Jiaotong University, Chengdu 611756, Sichuan, China
  • Received:2017-08-23 Online:2019-08-20 Published:2019-08-06
  • Contact: Tianrui LI E-mail:260226050@qq.com;trli@swjtu.edu.cn
  • Supported by:
    国家自然科学基金面上资助项目(61573292)

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Abstract:

ThemeRiver was a widely used technique when visualizing time-series data, which showed the whole trend efficiently. But the user often encountered ambiguity when observing a single river due to the influence of the lower river. However, the current visualization technique couldn't solve the issue. The following improvements of ThemeRiver were proposed upon the above issue: The river fluctuation was evaluated by the coefficient of variance instead of standard deviation, and the rivers with smaller fluctuation were arranged in lower position in order to reduce the impact on the upper rivers; The concept of ambiguity point was proposed, and the user could set fluctuation and max contribution as filtering parameters in the user interface so that the ambiguity points would be dynamically displayed by the system; The ambiguity point was visualized as bellow(The peak and valley of a river were represented by triangle and inverted triangle, respectively; The triangles would be filled with the color of the river with max contribution; A reorderable interactive ThemeRiver was proposed, in which the user was able to reorder the rivers by dragging them according to the information given by the ambiguity points). The proposed method was applied on the data containing 20 themes of 2015 from Zhihu and the results showed that the system could efficiently eliminate the ambiguity of ThemeRiver when presenting the trend of a single river and provided a flexible and personalized visualization.

Key words: visualization, ThemeRiver, time-series, coefficient of variance, interaction

CLC Number: 

  • TP391.1

Fig.1

Example of ambiguity point"

Fig.2

Schematic diagram of partial fluctuation"

Fig.3

Visualization design of ambiguity point"

Fig.4

Design of detail box"

Fig.5

Interactive design of ambiguity point filtering"

Fig.6

Result of river reordering"

Table 1

List of themes"

主题名称 主题id
教育 19553176
音乐 19550453
电影 19550429
美食 19551137
旅行 19551556
时尚 19551052
健身 19552192
游戏 19550994
动漫 19591985
商业 19555457

Table 2

CV of themes"

主题id 离散系数CV
19555457 4.575 840 95
19591985 4.441 672 33
19550994 3.925 709 49
19552192 3.375 679 73
19551052 3.188 013 32
19551137 2.710 706 00
19550429 2.419 658 42
19551556 2.845 386 74
19550453 2.152 558 57
19553176 1.974 204 42

Table 3

Order of themerivers"

河流层数 主题id(优化前) 主题id(优化后)
1 19555457 19553176
2 19591985 19550453
3 19550994 19550429
4 19552192 19551137
5 19551052 19551556
6 19551137 19551052
7 19550429 19552192
8 19551556 19550994
9 19550453 19591985
10 19553176 19555457

Table 4

Result of themerivers reordering"

河流层数 离散系数(优化前) 离散系数(优化后)
1 4.575 841 02 1.97 420 440
2 3.229 129 29 1.685 311 05
3 3.144 264 85 1.460 933 59
4 2.539 484 20 1.369 912 87
5 2.011 793 01 1.293 206 15
6 1.720 135 10 1.216 612 53
7 1.668 863 66 1.164 085 16
8 1.536 073 65 1.169 589 10
9 1.454 528 34 1.220 944 50
10 1.195 745 47 1.195 745 47
均值 2.307 585 86 1.375 054 48

Fig.7

Overview of the system"

Fig.8

Design of ambiguity point"

Fig.9

Result of river reordering"

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