Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Combining collaborative filtering with personal agents for better recommendations
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Developing a context-aware electronic tourist guide: some issues and experiences
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
A Framework for Collaborative, Content-Based and Demographic Filtering
Artificial Intelligence Review - Special issue on data mining on the Internet
Data mining: concepts and techniques
Data mining: concepts and techniques
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Getting to know you: learning new user preferences in recommender systems
Proceedings of the 7th international conference on Intelligent user interfaces
A Survey of Context-Aware Mobile Computing Research
A Survey of Context-Aware Mobile Computing Research
A Personalized Restaurant Recommender Agent for Mobile E-Service
EEE '04 Proceedings of the 2004 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'04)
Safety High Accuracy Context-Aware Matrix (CAM) Making Based on X.509 Proxy Certificate
ISA '09 Proceedings of the 3rd International Conference and Workshops on Advances in Information Security and Assurance
A Spatial User Similarity Measure for Geographic Recommender Systems
GeoS '09 Proceedings of the 3rd International Conference on GeoSpatial Semantics
Context-based services selection and recommendation through P-learning platform
ITHET'10 Proceedings of the 9th international conference on Information technology based higher education and training
Context-aware recommendation using rough set model and collaborative filtering
Artificial Intelligence Review
Using geospatial metadata to boost collaborative filtering
Proceedings of the 7th ACM conference on Recommender systems
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Utilizing Global Positioning System (GPS) technology, it is possible to find and recommend restaurants for users operating mobile devices. For recommending restaurants, Personal Digital Assistants or cellular phones only consider the location of restaurants. However, a user's background and environment information is assumed to be directly related to recommendation quality. In this paper, therefore, a recommender system using context information and a decision tree model for efficient recommendation is presented. This system considers location context, personal context, environment context, and user preference. Restaurant lists are obtained from location context, personal context, and environment context using the decision tree model. In addition, a weight value is used for reflecting user preferences. Finally, the system recommends appropriate restaurants to the mobile user. For this experiment, performance was verified using measurements such as k-fold cross-validation and Mean Absolute Error. As a result, the proposed system obtained an improvement in recommendation performance.