TY - GEN
T1 - A2W: Context-Aware Recommendation System for Mobile Augmented Reality Web Browser
AU - Lam, Kit Yung
AU - Lee, Lik Hang
AU - Hui, Pan
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/10
Y1 - 2021/10
N2 - Augmented Reality (AR) offers new capabilities for blurring the boundaries between physical reality and digital media. However, the capabilities of integrating web contents and AR remain underexplored. This paper presents an AR web browser with an integrated context-aware AR-to-Web content recommendation service named as A2W browser, to provide continuously user-centric web browsing experiences driven by AR headsets. We implement the A2W browser on an AR headset as our demonstration application, demonstrating the features and performance of A2W framework. The A2W browser visualizes the AR-driven web contents to the user, which is suggested by the content-based filtering model in our recommendation system. In our experiments, 20 participants with the adaptive UIs and recommendation system in A2W browser achieve up to 30.69% time saving compared to smartphone conditions. Accordingly, A2W-supported web browsing on workstations facilitates the recommended information leading to 41.67% faster reaches to the target information than typical web browsing.
AB - Augmented Reality (AR) offers new capabilities for blurring the boundaries between physical reality and digital media. However, the capabilities of integrating web contents and AR remain underexplored. This paper presents an AR web browser with an integrated context-aware AR-to-Web content recommendation service named as A2W browser, to provide continuously user-centric web browsing experiences driven by AR headsets. We implement the A2W browser on an AR headset as our demonstration application, demonstrating the features and performance of A2W framework. The A2W browser visualizes the AR-driven web contents to the user, which is suggested by the content-based filtering model in our recommendation system. In our experiments, 20 participants with the adaptive UIs and recommendation system in A2W browser achieve up to 30.69% time saving compared to smartphone conditions. Accordingly, A2W-supported web browsing on workstations facilitates the recommended information leading to 41.67% faster reaches to the target information than typical web browsing.
KW - augmented reality
KW - interaction in-the-wild
KW - mixed reality
KW - multi-device collaboration
KW - recommendation systems
KW - web browser
UR - http://www.scopus.com/inward/record.url?scp=85119367796&partnerID=8YFLogxK
U2 - 10.1145/3474085.3475413
DO - 10.1145/3474085.3475413
M3 - Conference article published in proceeding or book
AN - SCOPUS:85119367796
T3 - MM 2021 - Proceedings of the 29th ACM International Conference on Multimedia
SP - 2447
EP - 2455
BT - MM 2021 - Proceedings of the 29th ACM International Conference on Multimedia
PB - Association for Computing Machinery, Inc
T2 - 29th ACM International Conference on Multimedia, MM 2021
Y2 - 20 October 2021 through 24 October 2021
ER -