Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Collectively defining context in a mobile, networked computing environment
CHI '01 Extended Abstracts on Human Factors in Computing Systems
Cheese: tracking mouse movement activity on websites, a tool for user modeling
CHI '01 Extended Abstracts on Human Factors in Computing Systems
Discovery of Spatial Association Rules in Geographic Information Databases
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
Using ontologies in personalized mobile applications
Proceedings of the 12th annual ACM international workshop on Geographic information systems
Multimodal interactive maps: designing for human performance
Human-Computer Interaction
Managing spatial knowledge for mobile personalized applications
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV
Combining speech and pen input for effective interaction in mobile geospatial environments
Proceedings of the 2006 ACM symposium on Applied computing
Personalised maps in multimodal mobile GIS
International Journal of Web Engineering and Technology
Less-conscious information retrieval techniques for location based services
Proceedings of the 2009 International Workshop on Location Based Social Networks
GeminiMap - geographical enhanced map interface for navigation on the internet
W2GIS'07 Proceedings of the 7th international conference on Web and wireless geographical information systems
Association rule mining for mobile map personalisation
International Journal of Intelligent Systems Technologies and Applications
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When attempting to locate specific spatial information online users face the burden of having to differentiate between relevant and extraneous spatial content. This problem is more evident in the mobile environment where users are impeded by several device limitations. One way of overcoming this is to automatically profile users' spatial content preferences by recording all interactions users have with maps and monitoring users' movements in the field as they interact with maps. We describe a multimodal mobile GIS that implicitly records all user movements, as well as interactions between users and maps, to dynamically recommend information and to infer persistent spatial information preferences. A search engine, prefetching context-aware information, is incorporated to enhance the users' experiences. Modeling preferences in this manner allows us to recommend personalized context-aware spatial content to users whenever they request maps. A specific case study has been developed around subjects working on surveying tasks where spatial information is required in the field.