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基于神经网络的汽车说明书问答系统

A Car Manual Question Answering System Based on Neural Network
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摘要 为了简化用户查阅汽车说明书的流程,设计了针对中文汽车说明书的问答系统(CM-QA),包括以下3个问题:1)如何充分利用文档信息表示文档;2)领域词汇的分词和复述问题;3)正负样本不均衡。为了解决上述问题,结合卷积神经网络和双向长短时记忆网络对文本建模,手工构建领域词的复述词典,并使用字向量替代词向量。最后,尝试将模型转换为基于Pairwise思想的排序模型和扩展正例两种训练策略来解决正负样本不均衡的问题。在800条人工标注的问题上对系统进行了测试,其准确率达到了93.07%。 In order to simply the process for users to read the car manual,we construct a new QA system on the Chinese car manual.We call it Car Manual Question Answering(CM-QA)System.The goal of this task is to find the document with the relevant answers in the manual when given a question.This system includes three difficulties:(1)How to make use of all the information in the document.(2)This task contains a large number of domain words.Each domain word has not only one segmentation results and paraphrases.(3)The proportion of positive and negative cases in the corpus is extremely uneven.To solve these problems,we model the question and document by Convolution Neural Network(CNN)and bidirectional Long Short Time Memory(Bi-LSTM).and we replace the word vector representations with character vector representations and construct a paraphrase dictionary of domain words by hand.Finally,we design two different training strategies,namely,transforming the model into a ranking model based on pairwise method and expanding the positive case,so as to improve the imbalance between positive and negative cases.We test our system on 800hand-build test samples,with the accuracy of 93.07%.
作者 齐乐 张宇 马文涛 崔一鸣 王士进 刘挺 QI Le;ZHANG Yu;MA Wentao;CUI Yiming;WANG Shijin;LIU Ting(Research Center for Social Computing and Information Retrieval, Harbin Institute of Technology,Harbin 150001 ,China;Joint Laboratory of HIT and iFLYTEK ,iFLYTEK Research ,Beijing 100094,China)
出处 《山西大学学报:自然科学版》 CAS 北大核心 2019年第1期69-77,共9页 Journal of Shanxi University (Natural Science Edition)
基金 国家重点基础研究发展计划(973)(2014CB340503) 国家自然科学基金(61472105 61502120).
关键词 问答系统 神经网络 汽车说明书 自然语言处理 question answering system neural network car manual natural language processing
作者简介 齐乐(1994-),博士研究生,研究方向为自然语言处理。E-mail:lqi@ir.hit.edu.cn;通信作者:张宇(ZHANG Yu),E-mail:zhangyu@ir.hit.edu.cn.
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