KEYNET: An architecture and protocol for high-performance semantically rich information retrieval

We propose an architecture and protocol for semantically rich information retrieval from a subject-speci c corpus of information objects. The technique assumes that information objects have been labeled using small directed graphs, called content labels. A content label subsumes the role of an abstract. Both content labels and queries are required to conform with a general framework (ontology) for the subject area. Our method avoids explicit isomorphism testing by decomposing queries into fragments of small maximum size and using tables of these fragments to accomplish comparisons. The index structure is compatible with distributed processing architectures and scales up well, allowing very large collections to be searched very quickly using semantically complex queries.