Delivering personalized context-aware spatial information to mobile devices

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.