Open zengbin93 opened 6 years ago
BRITZ D. Deep Learning for Chatbots, Part 2 – Implementing a Retrieval-Based Model in Tensorflow[J]. WildML, 2016. 这是用Tensorflow实现一个检索型对话系统的介绍,查看数据和源码,请点击
End-to-End Task-Completion Neural Dialogue Systems[J]. 2017: 11. 微软发表的一个端到端实现TC-bot的方案,源码已经开源,源码1、源码2-python3
Learning End-to-End Goal-Oriented Dialog https://github.com/vyraun/chatbot-MemN2N-tensorflow
A Network-based End-to-End Trainable Task-oriented Dialogue System https://github.com/shawnwun/NNDIAL 阿里小蜜采用该方案实现
A Neural Conversational Model[J]. arXiv:1506.05869 [cs], 2015.
Smart Reply: Automated Response Suggestion for Email[J]. arXiv:1606.04870 [cs], 2016.
https://github.com/voicy-ai/DialogStateTracking 提供了两篇 end-to-end 方法实现
https://github.com/facebookresearch/DrQA Reading Wikipedia to Answer Open-Domain Questions
https://github.com/castorini/BuboQA Simple question answering over knowledge graphs (Mohammed et al., NAACL 2018)
https://github.com/S-H-Y-GitHub/QA 通过建立双向长短期记忆网络模型,实现了在多个句子中找到给定问题的答案所在的句子这一功能。
https://github.com/Conchylicultor/DeepQA tensorflow implementation of "A neural conversational model", a Deep learning based chatbot
https://github.com/NLPLearn/QANet Tensorflow implementation of QANet for machine reading comprehension
https://github.com/shashankg7/Keras-CNN-QA Keras (re)implementation of paper "Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks. SIGIR, 2015"
https://github.com/qhduan/Seq2Seq_Chatbot_QA 使用TensorFlow实现的Sequence to Sequence的聊天机器人模型
https://github.com/SnakeHacker/QA-Snake 基于多搜索引擎和深度学习技术的自动问答
https://github.com/Decalogue/chat 基于自然语言理解与机器学习的聊天机器人,支持多用户并发及自定义多轮对话
对话系统是一个可以与人进行交流的机器人,关于对话系统的详细介绍,请查看Wiki。