Graph4GUI: Graph Neural Networks for Representing Graphical User Interfaces

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

1 Sitaatiot (Scopus)
14 Lataukset (Pure)

Abstrakti

Present-day graphical user interfaces (GUIs) exhibit diverse arrangements of text, graphics, and interactive elements such as buttons and menus, but representations of GUIs have not kept up. They do not encapsulate both semantic and visuo-spatial relationships among elements. To seize machine learning’s potential for GUIs more efficiently, Graph4GUI exploits graph neural networks to capture individual elements’ properties and their semantic—visuo-spatial constraints in a layout. The learned representation demonstrated its effectiveness in multiple tasks, especially generating designs in a challenging GUI autocompletion task, which involved predicting the positions of remaining unplaced elements in a partially completed GUI. The new model’s suggestions showed alignment and visual appeal superior to the baseline method and received higher subjective ratings for preference. Furthermore, we demonstrate the practical benefits and efficiency advantages designers perceive when utilizing our model as an autocompletion plug-in.
AlkuperäiskieliEnglanti
OtsikkoCHI '24: Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems
ToimittajatFlorian Floyd Mueller, Penny Kyburz, Julie R. Williamson, Corina Sas, Max L. Wilson, Phoebe Toups Dugas, Irina Shklovski
KustantajaACM
Sivumäärä18
ISBN (elektroninen)979-8-4007-0330-0
DOI - pysyväislinkit
TilaJulkaistu - 11 toukok. 2024
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaACM SIGCHI Annual Conference on Human Factors in Computing Systems - Honolulu, USA, Honolulu, Yhdysvallat
Kesto: 11 toukok. 202416 toukok. 2024
https://chi2024.acm.org/

Conference

ConferenceACM SIGCHI Annual Conference on Human Factors in Computing Systems
LyhennettäACM CHI
Maa/AlueYhdysvallat
KaupunkiHonolulu
Ajanjakso11/05/202416/05/2024
www-osoite

Sormenjälki

Sukella tutkimusaiheisiin 'Graph4GUI: Graph Neural Networks for Representing Graphical User Interfaces'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.

Siteeraa tätä