Paper Info
Title
Using Dynamic Bayesian Networks to Model User-Experience.
Abstract
This paper presents a new approach to modelling the time course of user-experience (UX). Flexibility in modelling is essential: to select or develop UX models based on the outcome variables that are of interest in terms of explanation or prediction. At the same time, there is potential for (partial) re-using UX models across products and generalisation of models. As a case study, an experience model is developed for a particular consumer product, based on a time-sequential framework of subjective well-being [13] and a theoretical framework of flow for human-computer interaction [23]. The model is represented as a dynamic Bayesian network and the feasibility and limitations of using DBN are assessed. Future work will empirically evaluate the model with users of consumer products.
Year
DOI
Venue
2013
10.1007/978-3-642-55192-5_1
AGENTS AND DATA MINING INTERACTION (ADMI 2013)
Field
DocType
Volume
Data mining,User experience design,Computer science,Generalization,Augmented reality,Artificial intelligence,Machine learning,Dynamic Bayesian network
Conference
8316
ISSN
Citations 
PageRank 
0302-9743
0
0.34
References 
Authors
11
3
Name
Order
Citations
PageRank
Paul Van Schaik149936.74
Yifeng Zeng241543.27
Iain R. Spears351.45