Flytrap: intelligent group music recommendation
Proceedings of the 7th international conference on Intelligent user interfaces
More than the sum of its members: challenges for group recommender systems
Proceedings of the working conference on Advanced visual interfaces
Mobile Recommendation Systems for Decision Making "On the Go"
ICMB '05 Proceedings of the International Conference on Mobile Business
Adaptive radio: achieving consensus using negative preferences
GROUP '05 Proceedings of the 2005 international ACM SIGGROUP conference on Supporting group work
Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking
Proceedings of the 1st international conference on Mobile systems, applications and services
PolyLens: a recommender system for groups of users
ECSCW'01 Proceedings of the seventh conference on European Conference on Computer Supported Cooperative Work
Introduction to recommender systems
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Managing uncertainty in group recommending processes
User Modeling and User-Adapted Interaction
A Group Recommender System for Tourist Activities
EC-Web 2009 Proceedings of the 10th International Conference on E-Commerce and Web Technologies
Group recommendation: semantics and efficiency
Proceedings of the VLDB Endowment
The adaptive web
Design Research in Information Systems: Theory and Practice
Design Research in Information Systems: Theory and Practice
The needs of the many: a case-based group recommender system
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
| Hi-index | 0.00 |
Today's group recommender systems do not consider unavailable, inaccessible, or incomplete user information of one ore more members within a group. This is a problem for mobile group recommender system, because changed user behaviour or technical limitations of mobile services let user may not be willing or able to disclose all information, which are part of a user profile in a mobile environment. For location information, as one of the most important type of user information for an ad-hoc mobile recommendation service, this can lead to inaccurate, or missing location information. Inaccurate or missing location information has an impact on different parts of building group recommendations. This impact reduces the quality of recommendations, which is a key-challenge of recommender systems. Therefore, design guidelines are needed to address the problem of missing or inaccurate location information in mobile group recommender systems. This work describes the approach of building and validating those design guidelines and gives a first idea of impacts.