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Utilizing large-scale knowledge graphs to support inference at scale and explanation generation

机译:利用大规模知识图支持大规模推理和解释生成

摘要

Aspects discussed herein present a solution for utilizing large-scale knowledge graphs for inference at scale and generating explanations for the conclusions. In some embodiments, aspects discussed herein learn inference paths from a knowledge graph and determine a confidence score for each inference path. Aspects discussed herein may apply the inference paths to the knowledge graph to improve database lookup, keyword searches, inferences, etc. Aspects discussed herein may generate a natural language explanation for each conclusion or result from one or more inference paths that led to that conclusion or result. Aspects discussed herein may present the best conclusions or results to the user based on selection strategies. The presented results or conclusions may include generated natural language explanations rather than links to documents with word occurrences highlighted.
机译:本文讨论的方面提出了一种利用大规模知识图进行大规模推理并生成结论解释的解决方案。在一些实施例中,本文讨论的方面从知识图学习推理路径并确定每个推理路径的置信度得分。本文讨论的方面可以将推理路径应用于知识图,以改善数据库查找,关键字搜索,推理等。本文讨论的方面可以针对每个结论或来自导致该结论或结论的一个或多个推理路径的结果生成自然语言解释。结果。本文讨论的方面可以基于选择策略向用户呈现最佳结论或结果。呈现的结果或结论可能包括生成的自然语言解释,而不是带有突出显示单词出现的文档的链接。

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