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Abstract:
We present ANGIE, a system that can answer user queries by combining
knowledge
from a local database with knowledge retrieved from Web services. If a user
poses a query that cannot be answered by the local database alone, ANGIE
calls
the appropriate Web services to retrieve the missing information. In
ANGIE,Web
services act as dynamic components of the knowledge base that deliver
knowledge
on demand. To the user, this is fully transparent; the dynamically acquired
knowledge is presented as if it were stored in the local knowledge base.
We have developed a RDF based model for declarative definition of functions
embedded in the local knowledge base. The results of available Web
services are
cast into RDF subgraphs. Parameter bindings are automatically constructed by
ANGIE, services are invoked, and the semi-structured information returned by
the services are dynamically integrated into the knowledge base
We have developed a query rewriting algorithm that determines one or more
function composition that need to be executed in order to evaluate a
SPARQL style
user query. The key idea is that the local knowledge base can be used to
guide the selection of values used as input parameters of function
calls. This is in
contrast to the conventional approaches in the literature which would
exhaustively
materialize all values that can be used as binding values for the input
parameters.
