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Semantic‐Preserving Word Clouds by Seam Carving
Author(s) -
Wu Yingcai,
Provan Thomas,
Wei Furu,
Liu Shixia,
Ma KwanLiu
Publication year - 2011
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2011.01923.x
Subject(s) - computer science , seam carving , tag cloud , word (group theory) , visualization , cloud computing , carving , artificial intelligence , semantics (computer science) , information retrieval , image (mathematics) , natural language processing , mechanical engineering , philosophy , engineering , programming language , operating system , linguistics
Word clouds are proliferating on the Internet and have received much attention in visual analytics. Although word clouds can help users understand the major content of a document collection quickly, their ability to visually compare documents is limited. This paper introduces a new method to create semantic‐preserving word clouds by leveraging tailored seam carving, a well‐established content‐aware image resizing operator. The method can optimize a word cloud layout by removing a left‐to‐right or top‐to‐bottom seam iteratively and gracefully from the layout. Each seam is a connected path of low energy regions determined by a Gaussian‐based energy function. With seam carving, we can pack the word cloud compactly and effectively, while preserving its overall semantic structure. Furthermore, we design a set of interactive visualization techniques for the created word clouds to facilitate visual text analysis and comparison. Case studies are conducted to demonstrate the effectiveness and usefulness of our techniques.