Large scale knowledge base systems: an empirical evaluation perspective

Authors:
Yuanbo Guo;Abir Qasem;Jeff Heflin
Affiliations:
Computer Science & Engineering Department, Lehigh University, Bethlehem, PA;Computer Science & Engineering Department, Lehigh University, Bethlehem, PA;Computer Science & Engineering Department, Lehigh University, Bethlehem, PA
Venue:
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Year:
2006

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Abstract

In this paper, we discuss how our work on evaluating Semantic Web knowledge base systems (KBSs) contributes to address some broader AI problems. First, we show how our apprcach provides a benchmarking solution to the Semantic Web, a new application area of AI. Second, we discuss how the approach is also beneficial in a more traditional AI context. We focus on issues such as scalability, performance tradeoffs, and the comparison of different classes of systems.