Scalable Semantic Retrieval through Summarization and Refinement

Query processing of OWL-DL ontologies is intractable in the worst case, but we present a novel technique that in practice allows for efficient querying of ontologies with large Aboxes in secondary storage. We focus on the processing of instance retrieval queries, i.e., queries that retrieve individuals in the Abox which are instances of a given concept C. Our technique uses summarization and refinement to reduce instance retrieval to a small relevant subset of the original Abox. We demonstrate the effectiveness of this technique in Aboxes with up to 7 million assertions. Our results are applicable to the very expressive description logic SHIN, which corresponds to OWL-DL minus nominals and datatypes.

By: Julian Dolby; Achille Fokoue; Aditya Kalyanpur; Aaron Kershenbaum; Edith Schonberg; Kavitha Srinivas; Li Ma

Published in: RC24294 in 2007


This Research Report is available. This report has been submitted for publication outside of IBM and will probably be copyrighted if accepted for publication. It has been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be filled only by reprints or legally obtained copies of the article (e.g., payment of royalties). I have read and understand this notice and am a member of the scientific community outside or inside of IBM seeking a single copy only.


Questions about this service can be mailed to .