{"title":"移动应用的深度学习UI设计模式","authors":"Tam The Nguyen, P. Vu, H. Pham, T. Nguyen","doi":"10.1145/3183399.3183422","DOIUrl":null,"url":null,"abstract":"User interface (UI) is one of the most important components of a mobile app and strongly influences users' perception of the app. However, UI design tasks are typically manual and time-consuming. This paper proposes a novel approach to (semi)-automate those tasks. Our key idea is to develop and deploy advanced deep learning models based on recurrent neural networks (RNN) and generative adversarial networks (GAN) to learn UI design patterns from millions of currently available mobile apps. Once trained, those models can be used to search for UI design samples given user-provided descriptions written in natural language and generate professional-looking UI designs from simpler, less elegant design drafts.","PeriodicalId":212579,"journal":{"name":"2018 IEEE/ACM 40th International Conference on Software Engineering: New Ideas and Emerging Technologies Results (ICSE-NIER)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Deep Learning UI Design Patterns of Mobile Apps\",\"authors\":\"Tam The Nguyen, P. Vu, H. Pham, T. Nguyen\",\"doi\":\"10.1145/3183399.3183422\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"User interface (UI) is one of the most important components of a mobile app and strongly influences users' perception of the app. However, UI design tasks are typically manual and time-consuming. This paper proposes a novel approach to (semi)-automate those tasks. Our key idea is to develop and deploy advanced deep learning models based on recurrent neural networks (RNN) and generative adversarial networks (GAN) to learn UI design patterns from millions of currently available mobile apps. Once trained, those models can be used to search for UI design samples given user-provided descriptions written in natural language and generate professional-looking UI designs from simpler, less elegant design drafts.\",\"PeriodicalId\":212579,\"journal\":{\"name\":\"2018 IEEE/ACM 40th International Conference on Software Engineering: New Ideas and Emerging Technologies Results (ICSE-NIER)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE/ACM 40th International Conference on Software Engineering: New Ideas and Emerging Technologies Results (ICSE-NIER)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3183399.3183422\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE/ACM 40th International Conference on Software Engineering: New Ideas and Emerging Technologies Results (ICSE-NIER)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3183399.3183422","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
User interface (UI) is one of the most important components of a mobile app and strongly influences users' perception of the app. However, UI design tasks are typically manual and time-consuming. This paper proposes a novel approach to (semi)-automate those tasks. Our key idea is to develop and deploy advanced deep learning models based on recurrent neural networks (RNN) and generative adversarial networks (GAN) to learn UI design patterns from millions of currently available mobile apps. Once trained, those models can be used to search for UI design samples given user-provided descriptions written in natural language and generate professional-looking UI designs from simpler, less elegant design drafts.