Learning Efficient Truthful Mechanisms for Trading Networks
Takayuki Osogami, Segev Wasserkrug, et al.
IJCAI 2023
In the field of assistive technology, large scale user studies are hindered by the fact that potential participants are geographically sparse and longitudinal studies are often time consuming. In this contribution, we rely on remote usage data to perform large scale and long duration behavior anal-ysis on users of iMove, a mobile app that supports the orientation of people with visual impairments. Exploratory analysis highlights popular functions, com-mon configuration settings, and usage patterns among iMove users. The study shows stark differences between users ac-cessing the app through VoiceOver and other users, who tend to use the app more scarcely and sporadically. Analysis through clustering of VoiceOver iMove user interactions discovers four distinct user groups: 1) users interested in surrounding points of interest, 2) users keeping the app active for long sessions while in movement, 3) users interacting in short bursts to inquire about current location, and 4) users querying in bursts about surrounding points of interest and addresses. Our analysis provides insights into iMove's user base and can inform decisions for tailoring the app to diverse user groups, developing future improvements of the software, or guiding the design process of similar assistive tools.
Takayuki Osogami, Segev Wasserkrug, et al.
IJCAI 2023
Laura Bégon-Lours, Elisabetta Morabito, et al.
MRS Fall Meeting 2023
Yangyang Xu, Yibo Xu, et al.
Mathematical Programming Computation
Craig Mahlasi, Sibusisiwe Makhanya, et al.
DS-I Africa Consortium Meeting 2023