Similarity-based query caching

Abstract

With the success of the semantic web infrastructures for storing and querying RDF data are gaining importance. A couple of systemsare available now that provide basic database functionality for RDF data. Compared to modern database systems, RDF storage technology stilllacks sophisticated optimization methods for query processing. Current work in this direction is mainly focussed on index structures for speedingup the access at triple level or for special queries. In this paper, we discuss semantic query caching as a high level optimization techniquefor RDF querying to supplement existing work on lower level techniques. Our approach for semantic caching is based on the notion of similarityof RDF queries determined by the costs of modifying the results of a previous query into the result for the actual one. We discuss the problemof subsumption for RDF queries, present a cost model and derive a similarity measure for RDF queries based on the cost model and the notionof graph edit distance.