Reasoning about knowledge
Adding data mining support to SPARQL via statistical relational learning methods
ESWC'08 Proceedings of the 5th European semantic web conference on The semantic web: research and applications
How and why pop-ups don't work: Pop-up prompted eye movements, user affect and decision making
Computers in Human Behavior
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In spite of constant technological advances, the nature of today's military conflicts has increased the importance of intelligence gathering by human observers. To allow for efficient exploitation, the information collected needs to be structured. Traditional hand-held reporting systems solves this by assuming a fixed report structure; the reporter submits a report by filling in the various data fields in a predefined report schema. In this paper, we consider how to make the report schema aware of the reporting context and also dynamically adapt to information requests posed by actors external to the reporting situation: when a reporter enters data which are relevant to an information request, but do not fully answer the request, the schema expands to include fields that supply the missing information. We consider in detail how to evaluate relevance and how to select the additional data fields to query for. When deciding what additional data fields to query for, we take into account not merely what data is missing, but also the information capability of the reporter, i.e., what kind of data the reporter is in a position to supply in the context he or she is in; more technically, we assume that the information capabilities of reporters are formalized in a simple epistemic logic extension to the domain ontology that underlies the reporting system, and use reasoning to infer the appropriate additional data fields for which to query the reporter.