User Preferences and Recommendations
Pervasive applications assist human users to perform various tasks. In particular, these applications should become smart in the sense that even though the users may not explicitly specify their needs, the applications can learn from past interactions with users and adapt their behaviors in the future to provide customized services. In order to achieve this goal, pervasive applications actually learn user preferences from user interactions and make recommendations based on the learned preferences.
A recommendation is a way to help people find information to suit their needs and is widely used by many online services for suggesting products to customers that they might like to buy. For instance, Amazon ...
Get Pervasive Computing now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
