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Method and system for ranking and summarizing natural language passages

机译:用于对自然语言段落进行排名和总结的方法和系统

摘要

Examples of the present disclosure describe systems and methods relating to generating a relevance score on a given natural language answer to a natural language query for ranking the answer among other answers for the query, while generating a summary passage and a likely query to the given passage. For instance, multi-layered, recurrent neural networks may be used to encode the query and the passage, along with a multi-layered neural network for information retrieval features, to generate a relevant score for the passage. A multi-layered, recurrent neural network with soft attention and sequence-to-sequence learning task may be used as a decoder to generate a summary passage. A common encoding neural network may be employed to encode the passage for the ranking and the summarizing, in order to present concise and accurate natural language answers to the query.
机译:本公开的示例描述了与以下系统和方法有关的系统和方法,该系统和方法与针对自然语言查询的给定自然语言答案上的相关性分数相关,以对该查询的其他答案中的答案进行排名,同时生成摘要段落和对该给定段落的可能查询。例如,多层的递归神经网络可用于对查询和段落进行编码,以及用于信息检索特征的多层神经网络,以生成段落的相关分数。具有软注意力和序列到序列学习任务的多层递归神经网络可以用作解码器以生成摘要段落。可以采用通用的编码神经网络对段落进行排名和汇总编码,以便为查询提供简洁准确的自然语言答案。

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