Enrico: A Dataset for Topic Modeling of Mobile UI Designs

Luis A. Leiva, Asutosh Hota, Antti Oulasvirta

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaAbstractScientificvertaisarvioitu

9 Sitaatiot (Scopus)

Abstrakti

Topic modeling of user interfaces (UIs), also known as layout design categorization, contributes to a better understanding of the UI functionality. Starting from Rico, a large dataset of mobile UIs, we revised a random sample of 10k UIs and concluded to Enrico (shorthand of Enhanced Rico), a human-supervised high-quality dataset comprising 1460 UIs and 20 design topics. As a validation example, we train a deep learning model for three different UI representations (screenshots, wireframes, and embeddings). The screenshot representation provides the highest discriminative power (95% AUC) and a competitive accuracy of 75% (a random classifier achieves 5% accuracy in the same task). We discuss several applications that can be developed with this new public resource, including e.g. semantic UI captioning and tagging, explainable UI designs, smart tutorials, and improved design search capabilities.

AlkuperäiskieliEnglanti
DOI - pysyväislinkit
TilaJulkaistu - 10 toukok. 2020
OKM-julkaisutyyppiEi oikeutettu
TapahtumaInternational Conference on Human-Computer Interaction with Mobile Devices and Services - Oldenburg, Saksa
Kesto: 5 lokak. 20209 lokak. 2020
Konferenssinumero: 22

Conference

ConferenceInternational Conference on Human-Computer Interaction with Mobile Devices and Services
LyhennettäMobileHCI
Maa/AlueSaksa
KaupunkiOldenburg
Ajanjakso05/10/202009/10/2020

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