计算机科学 ›› 2022, Vol. 49 ›› Issue (5): 194-199.doi: 10.11896/jsjkx.210400195
钟将1, 尹红1, 张剑2
ZHONG Jiang1, YIN Hong1, ZHANG Jian2
摘要： 计算机领域知识快速更新且存在较多歧义,导致学生自主创新时难以找到合理的解决方案。作为辅助创新工具,智能问答系统可以协助学生更快地把握学科发展前沿,精准地找出解决问题的方法。在大规模科技文献库上构建科研知识图谱,实现了辅助学生创新的智能问答系统。为了减小查询问句中噪声实体带来的影响,提出一种基于辅助任务的意图信息增强神经网络(Auxiliary Task Enhanced Intent Information for Question Answering in Computer Domain,ATEI-QA)。相比传统方法,该方法能够更精确地提取问句意图信息,减小噪声实体给意图识别带来的影响。在计算机领域数据集和通用数据集上与3个主流模型开展了对比实验,结果表明所提模型在领域数据集上的MAP和MRR值平均提升了3.27%和1.72%,在通用数据集上的MAP和MRR值平均提升了4.37%和2.81%。
中图分类号:
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