Learning Situation Hyper-Graphs for Video Question Answering
Aisha Urooj Khan, Hilde Kuehne, et al.
CVPR 2023
This paper describes the evaluation of a natural language dialog-based navigation system (HappyAssistant) that helps users access e-commerce sites to find relevant information about products and services. The prototype system leverages technologies in natural language processing and human-computer interaction to create a faster and more intuitive way of interacting with websites, especially for less experienced users. The result of a comparative study shows that users prefer the natural language-enabled navigation two to one over the menu driven navigation. In addition, the study confirmed the efficiency of using natural language dialog in terms of the number of clicks and the amount of time required to obtain the relevant information. In the case study, as compared to the menu driven system, the average number of clicks used in the natural language system was reduced by 63.2% and the average time was reduced by 33.3%.
Aisha Urooj Khan, Hilde Kuehne, et al.
CVPR 2023
C.H. Morimoto, D. Koons, et al.
Image and Vision Computing
Dorit Nuzman, David Maze, et al.
SYSTOR 2011
Silvio Savarese, Holly Rushmeier, et al.
Proceedings of the IEEE International Conference on Computer Vision