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Intelligent Chinese Typesetting Model Based on Information Importance Can Enhance Text Readability.

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Title: Intelligent Chinese Typesetting Model Based on Information Importance Can Enhance Text Readability.
Authors: Ren, Hui (AUTHOR), Yan, Tao (AUTHOR), Chen, Xianglong (AUTHOR), Lyu, Ruimin (AUTHOR), Liu, Yuan (AUTHOR)
Source: International Journal of Human-Computer Interaction. May2025, Vol. 41 Issue 10, p6266-6285. 20p.
Subjects: Information overload, Chinese language, Websites, Data visualization, Readability formulas, Eye tracking
Abstract: In today's era of information overload, efficiently extracting valuable information from a large volume of textual data has become a crucial challenge in reading. This study aimed to explore the enhancement of Chinese readability in the digital domain through intelligent typesetting method. This study involved two experiments. The purpose of the first experiment was to achieve the machine learning-based assessment of the importance of individual words in Chinese articles and to automate typesetting based on the importance of words. For the second experiment, readability tests and eye-tracking reading tests were performed and the reading performance and reading attention between intelligent typesetting and general typesetting style was compared. This work proposed three Chinese typesetting methods that distinguished the importance of Chinese text information, based on font size and color. The results showed that first, when reading Chinese text, visual attention was more likely to be drawn to larger font sizes, darker brightness, or warmer-colored characters. Second, intelligent Chinese typography that distinguishes information importance through font size, color brightness, and color hue can enhance Chinese reading comprehension accuracy and subjective evaluation. It was concluded that using the TextRank model to distinguish importance of Chinese vocabulary and intelligent typesetting methods based on visual features of font could obviously improve text readability. Specifically, readability achieved through intelligent typesetting method distinguishing information importance through font color brightness surpasses that of general typesetting significantly. These intelligent typesetting methods can be widely applied in Chinese reading scenarios, such as web pages, e-books, information visualization, and other Chinese reading contexts. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Label: Title
  Group: Ti
  Data: Intelligent Chinese Typesetting Model Based on Information Importance Can Enhance Text Readability.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Ren%2C+Hui%22">Ren, Hui</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yan%2C+Tao%22">Yan, Tao</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chen%2C+Xianglong%22">Chen, Xianglong</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lyu%2C+Ruimin%22">Lyu, Ruimin</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Yuan%22">Liu, Yuan</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Human-Computer+Interaction%22">International Journal of Human-Computer Interaction</searchLink>. May2025, Vol. 41 Issue 10, p6266-6285. 20p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Information+overload%22">Information overload</searchLink><br /><searchLink fieldCode="DE" term="%22Chinese+language%22">Chinese language</searchLink><br /><searchLink fieldCode="DE" term="%22Websites%22">Websites</searchLink><br /><searchLink fieldCode="DE" term="%22Data+visualization%22">Data visualization</searchLink><br /><searchLink fieldCode="DE" term="%22Readability+formulas%22">Readability formulas</searchLink><br /><searchLink fieldCode="DE" term="%22Eye+tracking%22">Eye tracking</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In today's era of information overload, efficiently extracting valuable information from a large volume of textual data has become a crucial challenge in reading. This study aimed to explore the enhancement of Chinese readability in the digital domain through intelligent typesetting method. This study involved two experiments. The purpose of the first experiment was to achieve the machine learning-based assessment of the importance of individual words in Chinese articles and to automate typesetting based on the importance of words. For the second experiment, readability tests and eye-tracking reading tests were performed and the reading performance and reading attention between intelligent typesetting and general typesetting style was compared. This work proposed three Chinese typesetting methods that distinguished the importance of Chinese text information, based on font size and color. The results showed that first, when reading Chinese text, visual attention was more likely to be drawn to larger font sizes, darker brightness, or warmer-colored characters. Second, intelligent Chinese typography that distinguishes information importance through font size, color brightness, and color hue can enhance Chinese reading comprehension accuracy and subjective evaluation. It was concluded that using the TextRank model to distinguish importance of Chinese vocabulary and intelligent typesetting methods based on visual features of font could obviously improve text readability. Specifically, readability achieved through intelligent typesetting method distinguishing information importance through font color brightness surpasses that of general typesetting significantly. These intelligent typesetting methods can be widely applied in Chinese reading scenarios, such as web pages, e-books, information visualization, and other Chinese reading contexts. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/10447318.2024.2375799
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              Text: May2025
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