Rico: A Mobile App Dataset for Building Data-Driven Design Applications

被引：222

作者：

Deka, Biplab ^{[1
]}

Huang, Zifeng ^{[1
]}

Franzen, Chad ^{[1
]}

Hibschman, Joshua ^{[2
]}

Afergan, Daniel ^{[3
]}

Li, Yang ^{[3
]}

Nichols, Jeffrey ^{[3
]}

Kumar, Ranjitha ^{[1
]}

机构：

[1] Univ Illinois, Champaign, IL 61820 USA

[2] Northwestern Univ, Evanston, IL 60208 USA

[3] Google Inc, Mountain View, CA USA

来源：

UIST'17: PROCEEDINGS OF THE 30TH ANNUAL ACM SYMPOSIUM ON USER INTERFACE SOFTWARE AND TECHNOLOGY | 2017年

关键词：

Mobile app design; design mining; design search; app datasets;

D O I：

10.1145/3126594.3126651

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Data-driven models help mobile app designers understand best practices and trends, and can be used to make predictions about design performance and support the creation of adaptive UIs. This paper presents Rico, the largest repository of mobile app designs to date, created to support five classes of data-driven applications: design search, UI layout generation, Ut code generation, user interaction modeling, and user perception prediction. To create Rico, we built a system that combines crowdsourcing and automation to scalably mine design and interaction data from Android apps at runtime. The Rico dataset contains design data from more than 9.7k Android apps spanning 27 categories. It exposes visual, textual, structural, and interactive design properties of more than 72k unique UI screens. To demonstrate the kinds of applications that Rico enables, we present results from training an autoencoder for UI layout similarity, which supports query-by-example search over UIs,

引用

页码：845 / 854

页数：10

共 50 条

[1] Design and applications of an IoT architecture for data-driven smart building operations and experimentation
Malkawi, Ali
Ervin, Stephen
Han, Xu
Chen, Elence Xinzhu
Lim, Sunghwan
Ampanavos, Spyridon
Howard, Peter
[J]. ENERGY AND BUILDINGS, 2023, 295
[2] Mobile Data Science: Towards Understanding Data-Driven Intelligent Mobile Applications
Sarker, Iqbal H.
[J]. EAI ENDORSED TRANSACTIONS ON SCALABLE INFORMATION SYSTEMS, 2018, 5 (19) : 1 - 11
[3] Data-driven promotion planning for paid mobile applications
Li, Manqi
Huang, Yan
Sinha, Amitabh
[J]. Information Systems Research, 2020, 31 (03): : 1007 - 1029
[4] Data-Driven Promotion Planning for Paid Mobile Applications
Li, Manqi
Huang, Yan
Sinha, Amitabh
[J]. INFORMATION SYSTEMS RESEARCH, 2020, 31 (03) : 1007 - 1029
[5] A Consensus Compound/Bioactivity Dataset for Data-Driven Drug Design and Chemogenomics
Isigkeit, Laura
Chaikuad, Apirat
Merk, Daniel
[J]. MOLECULES, 2022, 27 (08):
[6] BIKED: A DATASET AND MACHINE LEARNING BENCHMARKS FOR DATA-DRIVEN BICYCLE DESIGN
Regenwetter, Lyle
Curry, Brent
Ahmed, Faez
[J]. PROCEEDINGS OF ASME 2021 INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE, IDETC-CIE2021, VOL 3A, 2021,
[7] SeeQ: A Programming Model for Portable Data-driven Building Applications
Mavrokapnidis, Dimitris
Fierro, Gabe
Husmann, Maria
Korolija, Ivan
Rovas, Dimitrios
[J]. PROCEEDINGS OF THE 10TH ACM INTERNATIONAL CONFERENCE ON SYSTEMS FOR ENERGY-EFFICIENT BUILDINGS, CITIES, AND TRANSPORTATION, BUILDSYS 2023, 2023, : 159 - 168
[8] Data-Driven Web APIs Recommendation for Building Web Applications
Qi, Lianyong
He, Qiang
Chen, Feifei
Zhang, Xuyun
Dou, Wanchun
Ni, Qiang
[J]. IEEE TRANSACTIONS ON BIG DATA, 2022, 8 (03) : 685 - 698
[9] Implementing data-driven parametric building design with a flexible toolbox
Brown, Nathan C.
Jusiega, Violetta
Mueller, Caitlin T.
[J]. AUTOMATION IN CONSTRUCTION, 2020, 118
[10] Data-Driven Design
Schmidt, Aaron
[J]. LIBRARY JOURNAL, 2016, 141 (06) : 26 - 26

← 1 2 3 4 5 →