BDBC-KG-NLP/QA-Survey-CN
北京航空航天大学大数据高精尖中心自然语言处理研究团队开展了智能问答的研究与应用总结。包括基于知识图谱的问答（KBQA），基于文本的问答系统（TextQA），基于表格的问答系统（TableQA）、基于视觉的问答系统（VisualQA）和机器阅读理解（MRC）等，每类任务分别对学术界和工业界进行了相关总结。
Comprehensive survey organizing QA research across eight subcategories—splitting academic and industrial approaches for CQA, MRC, and KBQA, while covering emerging TableQA and VQA tasks. Features domain-specific implementations including a Chinese reading comprehension pretraining model and a cross-domain knowledge interaction platform supporting rapid KBQA deployment. Actively tracks conference proceedings (ACL, EMNLP, CVPR, ICCV) with iterative updates, patents, and production systems deployed across aviation and general knowledge domains.
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