[1]TAO Ying,CHENG Yuxia,ZENG Zhenyu,et al.Intelligent generation and fine tuning of style based on the historical excellent layouts of digital newspapers[J].CAAI Transactions on Intelligent Systems,2024,19(4):930-940.[doi:10.11992/tis.202207021]
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Intelligent generation and fine tuning of style based on the historical excellent layouts of digital newspapers

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 19 Number of periods: 2024 4 Page number: 930-940 Column: 学术论文—智能系统 Public date: 2024-07-05
Title:
Intelligent generation and fine tuning of style based on the historical excellent layouts of digital newspapers
Author(s):
TAO Ying1;  CHENG Yuxia1;  ZENG Zhenyu1;  ZHUANG Yuehui2;  ZHANG Yixin1;  HE Xingzhen1
1. Computer College, Hangzhou Dianzi University, Hangzhou 310018, China;
2. Zhejiang Fangzheng Media Technology Research Institute, Jinhua 321099, China
Keywords:
layout automation; graphical design; design principle; image dataset; data-driven method; probability distribution; clustering; constraint programming
CLC:
TP391
DOI:
10.11992/tis.202207021
Abstract:
In traditional newspaper printing industry, designers need to manually typeset according to the design rules. The typesetting process is costly, time-consuming and labor-consuming. In order to improve the efficiency of typesetting, a method of automatic style generation and fine-tuning based on historical excellent layouts is proposed. In order to learn the style of newspaper typesetting from the data, an electronic newspaper database containing rich parameter information of design elements is created, which can effectively reflect the layout of newspapers. For a given news article, firstly, a probability model is trained according to the historical excellent layout to infer the layout style of the electronic newspaper, and the fixed constraints and user constraints are combined to ensure that the style is effective. At the same time, some aesthetic design principles are quantified to further realize style fine-tuning. Finally, through qualitative and quantitative evaluation, it shows that the new method can generate newspapers that meet the visual aesthetics, hierarchy and readability.This method can provide a reference for intelligent generation of layout design styles.
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