Indexing Real-World Data using Semi-Structured Documents

We address the problem of deriving meaningful semantic index information for a multi-media database using a semi-structured document model. We show how our framework, called feature grammars, can be used to (1) exploit third-party interpretation modules for real-world unstructured components, and (2) use context-free grammars to convert such poorly or unstructured input to semi-structured output. The basic idea is to enrich context-free grammars with special symbols called detectors, which provide for the necessary structure just-intime to satisfy a parser look-ahead. A prototype implementation has been constructed in the Acoi project to demonstrate the feasibility of this approach for indexing both images and audio documents. 1991 Computing Reviews Classification System: [H2.4,H.3.1] Multimedia indexing