KEYNET is a knowledge retrieval model and architecture based on the vector space model that unifies and extends many commonly used retrieval mechanisms. A distributed architecture, communication protocol and indexing algorithm for high-performance retrieval using this model has been developed. A prototype system has been built that achieves a throughput of 500 queries per second with a response time of less than one second on an 8-node network of workstations. The model and algorithm are designed for retrieval from a corpus of information objects in a single subject area. The objects need not be textual, and must be annotated with content labels. With current technology, the KEYNET system can be scaled up to support a corpus of several million information objects. Finally, the model allows for content labels that are semantically more complex than just attributes, keywords and subject classifications.
A distributed approach to high-performance information retrieval
KEYNET: Fast indexing for semantically rich information retrieval
High-Performance, Distributed Information Retrieval
KEYNET: An architecture and protocol for high-performance semantically rich information retrieval
A unified approach to high-performance, vector-based information retrieval