A progressive query language and interactive reasoner for information fusion support

Previous approaches in query processing do not consider queries to automatically combine results obtained from different information sources, i.e. they do not support information fusion. In this work, an approach for information fusion using a progressive query language and an interactive reasoner is for this reason introduced. The system basically consists of a query processor with fusion capability and a reasoner with learning capability. This query processor first executes a query to produce some initial results. If the initial results are uninformative, then the reasoner guided by the user creates a more elaborate query by means of some rule and returns the query to the query processor to produce a more informative answer. What is novel in our approach is that application-dependent information fusion rules can be initially specified by the user and subsequently learned by the reasoner. Examples of progressive queries are drawn from multi-sensor information fusion applications.