Human-machine cooperation with epistemological DBs: supporting user corrections to knowledge bases
AKBC-WEKEX '12 Proceedings of the Joint Workshop on Automatic Knowledge Base Construction and Web-scale Knowledge Extraction(2012)
摘要
Knowledge bases (KB) provide support for real-world decision making by exposing data in a structured format. However, constructing knowledge bases requires gathering data from many heterogeneous sources. Manual efforts for this task are accurate, but lack scalability, and automated approaches provide good coverage, but are not reliable enough for real-world decision makers to trust. These two approaches to KB construction have complementary strengths: in this paper we propose a novel framework for supporting humanproposed edits to knowledge bases.
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关键词
kb construction,human-machine cooperation,good coverage,lack scalability,complementary strength,heterogeneous source,user correction,real-world decision,automated approach,knowledge base,humanproposed edit,real-world decision maker,epistemological dbs
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