TY - GEN
T1 - An application of optimization method for storyline based on cluster analysis
AU - Liu, Yuhua
AU - Lin, Hanfei
AU - Liang, Yitao
AU - Wang, Changbo
N1 - Publisher Copyright:
© 2017 Copyright is held by the owner/author(s).
PY - 2017/8/14
Y1 - 2017/8/14
N2 - As a new visualization technology1, storyline intuitively illustrates the dynamic relationships between entities in a story, which is useful in many applications, including the description of characters' interactions in movies, the evolution of community structure in dynamic social networks, the marital status between people, etc. Previous works optimize the storyline's layout from the perspective of aesthetic standard, significantly reducing line crossings, line wiggles and layout space. But when dealing with large-scale data, there is room for improvement with regard to three issues: insufficient memory space, large time consumption and weak data expression. Therefore, this paper introduces the idea of cluster analysis to the storyline to present the clustering information and reduce the time complexity under the condition where a large number of entities interact in the same period. Meantime a scalable, reusable visualization library of storyline is implemented including some novel interactions.
AB - As a new visualization technology1, storyline intuitively illustrates the dynamic relationships between entities in a story, which is useful in many applications, including the description of characters' interactions in movies, the evolution of community structure in dynamic social networks, the marital status between people, etc. Previous works optimize the storyline's layout from the perspective of aesthetic standard, significantly reducing line crossings, line wiggles and layout space. But when dealing with large-scale data, there is room for improvement with regard to three issues: insufficient memory space, large time consumption and weak data expression. Therefore, this paper introduces the idea of cluster analysis to the storyline to present the clustering information and reduce the time complexity under the condition where a large number of entities interact in the same period. Meantime a scalable, reusable visualization library of storyline is implemented including some novel interactions.
KW - Cluster analysis
KW - Interaction
KW - Storyline
KW - Visualization
UR - https://www.scopus.com/pages/publications/85030783340
U2 - 10.1145/3105971.3105986
DO - 10.1145/3105971.3105986
M3 - 会议稿件
AN - SCOPUS:85030783340
T3 - ACM International Conference Proceeding Series
SP - 24
EP - 28
BT - VINCI 2017 - 10th International Symposium on Visual Information Communication and Interaction
A2 - Takahashi, Shigeo
A2 - Li, Jie
PB - Association for Computing Machinery
T2 - 10th International Symposium on Visual Information Communication and Interaction, VINCI 2017
Y2 - 14 August 2017 through 16 August 2017
ER -