摘要
由于要处理复杂的推理问题,同时要求处理输入序列生成输出序列,生成式自动问答系统被视为成为自然语言处理中一项困难的任务。Seq2Seq模型的提出为序列到序列的生成模型提供一个新的结构基础。基于Seq2Seq基础结构设计并实现一个轻量级的生成式自动问答模型。通过一个综合检验自动问答系统性能的数据集b Ab I-10k,验证与分析基于Seq2Seq的生成式自动问答系统模型在20种不同类型的推理任务上性能。
Requiring complex reasoning abilities, processing input sequence and generating output sequence, generative automatic question answer- ing system is regarded as a hard task in natural language processing. Seq2Seq provides a novel basic structure for the sequence-to-se- quence generation models. Designs and implements a generative automatic question and answer model which is based on Seq2Seq struc- ture. Evaluates on a synthesized question answering dataset bAbi-10k, analyzes the reasoning abilities of proposed question answering sys- tem on 20 different reasoning tasks.
出处
《现代计算机》
2017年第24期57-60,共4页
Modern Computer
基金
国家重点研发计划资助(No.2016YFC0801800)
大数据分析四川省青年科技创新研究团队(No.2016TD0018)
关键词
自动问答系统
自然语言处理
深度学习
回复式神经网络
Question Answering System
Natural Language Processing
Deep Learning
Recurrent Neural Networks