Shiang-Yi Chen

dblp:170/1688 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics › text visualization
tag cloud
0.212015
Morphable Word Clouds for Time-Varying Text Data Visualization · IEEE Trans. Vis. Comput. Graph. 2015
Visualization and visual analytics
text visualization
0.212015
Morphable Word Clouds for Time-Varying Text Data Visualization · IEEE Trans. Vis. Comput. Graph. 2015
Visualization and visual analytics › time series visualization
temporal trend visualization
0.112015
Morphable Word Clouds for Time-Varying Text Data Visualization · IEEE Trans. Vis. Comput. Graph. 2015

Methods — techniques the papers use, named apart from their topics

rigid body dynamics · 0.2layout optimization · 0.2
YearPublicationVenuePosition
2015 Morphable Word Clouds for Time-Varying Text Data Visualization
abstract
A word cloud is a visual representation of a collection of text documents that uses various font sizes, colors, and spaces to arrange and depict significant words. The majority of previous studies on time-varying word clouds focuses on layout optimization and temporal trend visualization. However, they do not fully consider the spatial shapes and temporal motions of word clouds, which are important factors for attracting people's attention and are also important cues for human visual systems in capturing information from time-varying text data. This paper presents a novel method that uses rigid body dynamics to arrange multi-temporal word-tags in a specific shape sequence under various constraints. Each word-tag is regarded as a rigid body in dynamics. With the aid of geometric, aesthetic, and temporal coherence constraints, the proposed method can generate a temporally morphable word cloud that not only arranges word-tags in their corresponding shapes but also smoothly transforms the shapes of word clouds over time, thus yielding a pleasing time-varying visualization. Using the proposed frame-by-frame and morphable word clouds, people can observe the overall story of a time-varying text data from the shape transition, and people can also observe the details from the word clouds in frames. Experimental results on various data demonstrate the feasibility and flexibility of the proposed method in morphable word cloud generation. In addition, an application that uses the proposed word clouds in a simulated exhibition demonstrates the usefulness of the proposed method.
Ming-Te Chi, Shih-Syun Lin, Shiang-Yi Chen, Chao-Hung Lin, Tong-Yee Lee
IEEE Trans. Vis. Comput. Graph.3