Abstract
We present the architecture of an end-to-end semantic search engine that uses a graph data model to enable interactive query
answering over structured and interlinked data collected from many disparate sources on the Web. In particular, we study distributedindexing methods for graph-structured data and parallel query evaluation methods on a cluster of computers. We evaluate thesystem on a dataset with 430 million statements collected from the Web, and provide scale-up experiments on 7 billion syntheticallygenerated statements.
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