Name
Abstract | ||
|---|---|---|
One of the driving applications of ubiquitous computing is universal appliance interaction. It is the ability to use arbitrary mobile devices-some of which we traditionally think of as computers (e.g. handhelds and wearables), and some of which we do not (e.g. cell phones)-to interact with arbitrary appliances such as TVs, printers, and lights. We believe that universal appliance interaction is best supported through the deployment of appliance user-interfaces (UIs) that are personalized to a user's habits and information needs. We are building a UI deployment system for universal appliance interaction to support various personalization features based on predicting a user's behavior. It is our belief that we can achieve these features in our system by modeling user actions using machine learning (ML) algorithms. The initial step in building such a system that relies on ML for prediction is to show that there are patterns in user appliance interaction. In this paper, our goal is to present evidence demonstrating these patterns. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1145/948542.948555 | Richard Tapia Celebration of Diversity in Computing Conference, 2003 |
Keywords | Field | DocType |
user modeling,personalized universal appliance interaction,universal appliance interaction,information need,user action,arbitrary appliance,user appliance interaction,arbitrary mobile devices-some,cell phone,ui deployment system,driving application,appliance user-interfaces,mobile device,ubiquitous computing,user model,machine learning,user interface,human computer interaction | Information needs,Software deployment,Wearable computer,Computer science,Human–computer interaction,User modeling,Ubiquitous computing,Multimedia,Personalization | Conference |
ISBN | Citations | PageRank |
1-58113-790-7 | 1 | 0.35 |
References | Authors | |
1 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Olufisayo Omojokun | 1 | 44 | 5.03 |
| Charles L. Isbell | 2 | 504 | 65.79 |