Design patterns: elements of reusable object-oriented software
Design patterns: elements of reusable object-oriented software
Towards a Better Understanding of Context and Context-Awareness
HUC '99 Proceedings of the 1st international symposium on Handheld and Ubiquitous Computing
A collaborative filtering algorithm and evaluation metric that accurately model the user experience
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
A survey on context-aware systems
International Journal of Ad Hoc and Ubiquitous Computing
Social recommender systems for web 2.0 folksonomies
Proceedings of the 20th ACM conference on Hypertext and hypermedia
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
Context awareness by case-based reasoning in a music recommendation system
UCS'07 Proceedings of the 4th international conference on Ubiquitous computing systems
Context-Aware Image Annotation and Retrieval on Mobile Device
MMIT '10 Proceedings of the 2010 Second International Conference on MultiMedia and Information Technology - Volume 01
SBCARS '10 Proceedings of the 2010 Fourth Brazilian Symposium on Software Components, Architectures and Reuse
Recommender Systems: An Introduction
Recommender Systems: An Introduction
Towards the semantic and context-aware management of mobile multimedia
Multimedia Tools and Applications
A Multimedia Semantic Recommender System for Cultural Heritage Applications
ICSC '11 Proceedings of the 2011 IEEE Fifth International Conference on Semantic Computing
Mobile exploration of geotagged photographs
Personal and Ubiquitous Computing
MapReduce performance evaluation for knowledge-based recommendation of context-tagged photos
Proceedings of the 19th Brazilian symposium on Multimedia and the web
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One of the most important challenges in Information Systems is information overload. Recommender Systems try to cope with this problem by helping people in retrieving information (ex: videos, services, products, images, etc.) that may match their preferences and intentions. An issue of Recommender Systems is related to user's context. The use of the system in a different context than usual may cause an unsatisfactory result for the recommendation, since preferences and intentions can be influenced by user's context (location, trajectory, time of day, activity, etc.). This paper presents the MMedia2U, a mobile photo recommender system that exploits the user's context and the context when photo was created as a means to improve the recommendation. Three context dimensions area exploited: spatial, social and temporal. We describe the similarity measures used for each dimension and the results of the system evaluation with 13 users following a Gold Standard approach.