Toward Webscale, Rule-Based Inference on the Semantic Web Via Data Parallelism.

摘要

This thesis considers the problem of scaling rule-based inference to large quantities of RDF data found on the Semantic Web. The general approach is one of data parallelism, that is, dividing data among processors such that the collective results of each