阿基米德:基于概率知识库的高效查询处理

SIGMOD Rec. Pub Date : 2017-09-01 DOI:10.1145/3137586.3137592

Yang Chen, Xiaofeng Zhou, Kun Li, Daisy Zhe Wang

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引用次数: 4

摘要

提出了一种基于概率知识库的高效查询处理的阿基米德系统。由于信息源和人类知识的限制，我们为包含不完整和不确定信息的知识库设计了阿基米德。回答对这些知识库的查询需要有效的概率推理。本文描述了ARCHIMEDES在数据库内统一的数据和图并行计算框架UDA-GIST上的高效知识扩展和查询驱动推理。凭借高效的推理引擎，阿基米德可以在大量不确定知识库的查询中产生合理的结果。我们使用Reverb-Sherlock和wikilinks知识库来显示阿基米德具有令人满意的质量和实时性能。

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Archimedes: Efficient Query Processing over Probabilistic Knowledge Bases

We present the ARCHIMEDES system for efficient query processing over probabilistic knowledge bases. We design ARCHIMEDES for knowledge bases containing incomplete and uncertain information due to limitations of information sources and human knowledge. Answering queries over these knowledge bases requires efficient probabilistic inference. In this paper, we describe ARCHIMEDES's efficient knowledge expansion and querydriven inference over UDA-GIST, an in-database unified data- and graph-parallel computation framework. With an efficient inference engine, ARCHIMEDES produces reasonable results for queries over large uncertain knowledge bases. We use the Reverb-Sherlock andWikilinks knowledge bases to show ARCHIMEDES achieves satisfactory quality with real-time performance.

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来源期刊

SIGMOD Rec.

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