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We describe our method for benchmarking Semantic Web knowledge base systems with respect to use in large OWL applications. We present the Lehigh University Benchmark (LUBM) as an example of how to design such benchmarks. The LUBM features an on-tology for the university domain, synthetic OWL data scalable to an arbitrary size, fourteen extensional queries(More)
Although search engine technology has improved in recent years, there are still many types of searches that return unsatisfactory results. This situation can be greatly improved if web pages use a semantic markup language to describe their content. We have developed SHOE, a language for this purpose, and in this paper describe a scenario for how the(More)
We present DLDB, a knowledge base system that extends a relational database management system with additional capabilities for DAML+OIL inference. We discuss a number of database schemas that can be used to store RDF data and discuss the tradeoffs of each. Then we describe how we extend our design to support DAML+OIL entailments. The most significant aspect(More)
In this paper, we present our work on evaluating knowledge base systems with respect to use in large OWL applications. To this end, we have developed the Lehigh University Benchmark (LUBM). The benchmark is intended to evaluate knowledge base systems with respect to extensional queries over a large dataset that commits to a single realistic ontology. LUBM(More)
the Web pages to the extent required to perform the desired tasks. An alternative is to change the Web to make it more understandable by machines, thereby creating a Semantic Web. Many researchers believe the key to building this new Web lies in the development of semantically enriched languages. Early languages, such as the resource description framework,1(More)
We discuss the problems associated with managing ontologies in distributed environments such as the Web. The Web poses unique problems for the use of ontologies because of the rapid evolution and autonomy of web sites. We present SHOE, a web-based knowledge representation language that supports multiple versions of ontologies. We describe SHOE in the terms(More)
XML will have a profound impact on the way data is exchanged on the Internet. An important feature of this language is the separation of content from presentation, which makes it easier to select and/or reformat the data. However, due to the likelihood of numerous industry and domain specific DTDs, those who wish to integrate information will still be faced(More)
This paper describes how SHOE, a set of Simple HTML Ontological Extensions, can be used to discover implicit knowledge from the World-Wide Web (WWW). SHOE allows authors to annotate their pages with ontology-based knowledge about page contents. In previous papers, we discussed how the semantic knowledge provided by SHOE allows users to issue queries that(More)