ContextPlayer: learning contextual music preferences for situational recommendations

Authors:
Karla Okada;Börje F. Karlsson;Laura Sardinha;Tomaz Noleto
Affiliations:
Nokia Institute of Technology (INdT), Manaus, AM, Brazil;Microsoft Research Asia Beijing, China;Nokia Institute of Technology (INdT), Manaus, AM, Brazil;Nokia Institute of Technology (INdT), Manaus, AM, Brazil
Venue:
SIGGRAPH Asia 2013 Symposium on Mobile Graphics and Interactive Applications
Year:
2013

Citing 12
Cited 0

Understanding and Using Context

Personal and Ubiquitous Computing
The usability engineering lifecycle

CHI '99 Extended Abstracts on Human Factors in Computing Systems
Designing mobile commerce applications

Communications of the ACM - Mobile computing opportunities and challenges
Out of context: computer systems that adapt to, and learn from, context

IBM Systems Journal
Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions

IEEE Transactions on Knowledge and Data Engineering
Observing the User Experience: A Practitioner's Guide to User Research (Morgan Kaufmann Series in Interactive Technologies) (The Morgan Kaufmann Series in Interactive Technologies)

Observing the User Experience: A Practitioner's Guide to User Research (Morgan Kaufmann Series in Interactive Technologies) (The Morgan Kaufmann Series in Interactive Technologies)
A survey on context-aware systems

International Journal of Ad Hoc and Ubiquitous Computing
A framework for evaluating the usability of mobile phones based on multi-level, hierarchical model of usability factors

Interacting with Computers
A survey of context modelling and reasoning techniques

Pervasive and Mobile Computing
Smartphone usage in the wild: a large-scale analysis of applications and context

ICMI '11 Proceedings of the 13th international conference on multimodal interfaces
Recommender systems: from algorithms to user experience

User Modeling and User-Adapted Interaction
Explaining the user experience of recommender systems

User Modeling and User-Adapted Interaction

Quantified Score

Hi-index	0.00

Visualization

Abstract

Music listening is a very personal and situational behaviour, which suggests that contextual information could be used to greatly enhance music recommendation experience. However, making such use of mobile context, while learning user profiles, is a challenging problem. This case study presents a system for collecting context and usage data from mobile devices, but targeted at recommending music via unsupervised learning of user profiles and relevant situations. The developed data flow system supports both short enough response times and longer asynchronous reasoning on the collected data; furthermore, the mobile phone acts not only as sensor, but the mobile app is directly tied to the effectiveness of the music service user experience (UX). This work describes our system design and discusses issues related to the problem space and to usability tests on such systems, based on an international user trial.