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)
Personalizing search via automated analysis of interests and activities
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Extracting metadata for spatially-aware information retrieval on the internet
Proceedings of the 2005 workshop on Geographic information retrieval
Implicit interaction profiling for recommending spatial content
Proceedings of the 13th annual ACM international workshop on Geographic information systems
Toward tighter integration of web search with a geographic information system
Proceedings of the 15th international conference on World Wide Web
Web information retrieval based on user operation on digital maps
GIS '06 Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems
Reranking and Classifying Search Results Exhaustively Based on Edit-and-Propagate Operations
DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
REJA: A Georeferenced Hybrid Recommender System for Restaurants
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Geographic information retrieval to suit immediate surroundings
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Geographical recommender system based on interaction between map operation and category selection
Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems
ACM SIGSOFT Software Engineering Notes
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Digital map services and search services for geographical information are widely available on the Internet. Users can retrieve suitable geographical information using these digital maps through certain map operations and category selections. However, when a map region includes a large amount of information, it can be difficult for users to find specific geographical information. In addition, a user's interest in a region or a category may change. Therefore, we propose a method for recommending geographical information to users on the basis of their map operation or category selection history. We develop a model for determining a user's interest and use it to recommend suitable regions and categories.