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  • 聊天机器人 (Chatbot) 专知荟萃

    • 入门学习

    • 进阶论文

    • 综述

    • 专门会议

    • Tutorial

    • 软件

      • Chatbot

      • Chinese_Chatbot

    • 数据集

    • 领域专家


聊天机器人 (Chatbot) 专知荟萃

入门学习

  1. 对话系统的历史(聊天机器人发展)

    • [http://blog.csdn.net/zhoubl668/article/details/8490310]

  2. 微软邓力：对话系统的分类与发展历程

    • [https://www.leiphone.com/news/201703/6PNNwLXouKQ3EyI5.html]

  3. Deep Learning for Chatbots, Part 1 – Introduction 聊天机器人中的深度学习技术之一：导读

    • [http://www.jeyzhang.com/deep-learning-for-chatbots-1.html]

    • [http://www.wildml.com/2016/04/deep-learning-for-chatbots-part-1-introduction/]

  4. Deep Learning for Chatbots, Part 2 – Implementing a Retrieval-Based Model in Tensorflow  聊天机器人中的深度学习技术之二：基于检索模型的实现

    • [http://www.jeyzhang.com/deep-learning-for-chatbots-2.html]

    • [http://www.wildml.com/2016/07/deep-learning-for-chatbots-2-retrieval-based-model-tensorflow/]

  5. 自己动手做聊天机器人教程（1-42）

    • [https://github.com/warmheartli/ChatBotCourse]

  6. 如何让人工智能助理杜绝“智障”  微软亚洲研究院

    • [http://www.msra.cn/zh-cn/news/features/virtual-personal-assistant-20170411]

  7. 周明：自然语言对话引擎  微软亚洲研究院

    • [http://www.msra.cn/zh-cn/news/features/ming-zhou-conversation-engine-20170413]

  8. 谢幸：用户画像、性格分析与聊天机器人

    • [http://www.msra.cn/zh-cn/news/features/xing-xie-speech-20170324]

  9. 25 Chatbot Platforms: A Comparative Table

    • [https://chatbotsjournal.com/25-chatbot-platforms-a-comparative-table-aeefc932eaff]

  10. 聊天机器人开发指南   IBM

    • [https://www.ibm.com/developerworks/cn/cognitive/library/cc-cognitive-chatbot-guide/index.html]

  11. 朱小燕：对话系统中的NLP

  12. 使用深度学习打造智能聊天机器人   张俊林

    • [http://blog.csdn.net/malefactor/article/details/51901115]

  13. 九款工具帮您打造属于自己的聊天机器人

    • [http://mobile.51cto.com/hot-520148.htm]

  14. 聊天机器人中对话模板的高效匹配方法

    • [http://blog.csdn.net/malefactor/article/details/52166235]

  15. 中国计算机学会通讯 2017年第9期   人机对话专刊

    • 对话系统评价技术进展及展望                   by 张伟男 车万翔

    • 人机对话                                                      by 刘 挺 张伟男

    • 任务型与问答型对话系统中的语言理解技术  by 车万翔 张 宇

    • 聊天机器人的技术及展望                            by 武 威 周 明

    • 人机对话中的情绪感知与表达                     by 黄民烈 朱小燕

    • 对话式交互与个性化推荐                            by 胡云华

    • 对话智能与认知型口语交互界面                  by 俞 凯

    • [https://pan.baidu.com/s/1o8Lv138]

  16. 中国人工智能学会通讯

    • 从图灵测试到智能信息获取                 郝 宇，朱小燕，黄民烈

    • 智能问答技术                                       何世柱，张元哲，刘 康，赵 军

    • 社区问答系统及相关技术                                 王 斌，吉宗诚

    • 聊天机器人技术的研究进展                              张伟男，刘 挺

    • 如何评价智能问答系统                                       黄萱菁

    • 智能助手: 走出科幻，步入现实                        赵世奇，吴华

    • [http://caai.cn/index.php?s=/Home/Article/qikandetail/year/2016/month/01.html]


进阶论文

  1. Sequence to Sequence Learning with Neural Networks

    • [http://papers.nips.cc/paper/5346-sequence-to-sequence-learning-with-neural-networks.pdf]

  2. A Neural Conversational Model   Oriol Vinyals, Quoc Le

    • [http://arxiv.org/pdf/1506.05869v1.pdf]

  3. A Diversity-Promoting Objective Function for Neural Conversation Models

  4. A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues

    • [https://arxiv.org/abs/1605.06069]

  5. Sequence to Backward and Forward Sequences: A Content-Introducing Approach to Generative Short-Text Conversation

    • [https://arxiv.org/abs/1607.00970]

  6.  A Persona-Based Neural Conversation Model

    • [https://arxiv.org/abs/1603.06155]

  7. Deep Reinforcement Learning for Dialogue Generation

    • [https://arxiv.org/abs/1606.01541]

  8.  End-to-end LSTM-based dialog control optimized with supervised and reinforcement learning

    • [https://arxiv.org/abs/1606.01269]

  9. A Network-based End-to-End Trainable Task-oriented Dialogue System

    • [https://arxiv.org/abs/1604.04562]

  10.  Incorporating Unstructured Textual Knowledge Sources into Neural Dialogue Systems

    • [http://www.iro.umontreal.ca/~lisa/publications2/index.php/publications/show/871]

  11. A Neural Network Approach to Context-Sensitive Generation of Conversational Responses

    • [https://arxiv.org/abs/1506.06714]

  12. A Dataset for Research on Short-Text Conversation

    • [http://staff.ustc.edu.cn/~cheneh/paper_pdf/2013/HaoWang.pdf\]

  13. The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems

    • [https://arxiv.org/abs/1506.08909]

  14. Joint Online Spoken Language Understanding and Language Modeling with Recurrent Neural Networks, 2016

    • [https://arxiv.org/abs/1609.01462]

  15. Neural Utterance Ranking Model for Conversational Dialogue Systems, 2016

    • [https://www.researchgate.net/publication/312250877_Neural_Utterance_Ranking_Model_for_Conversational_Dialogue_Systems\

  16. A Context-aware Natural Language Generator for Dialogue Systems, 2016

    • [https://arxiv.org/abs/1608.07076]

  17. Task Lineages: Dialog State Tracking for Flexible Interaction, 2016

    • [https://www.microsoft.com/en-us/research/publication/task-lineages-dialog-state-tracking-flexible-interaction-2/]

  18. Affective Neural Response Generation

    • [https://arxiv.org/abs/1709.03968]

  19. Multi-Task Learning for Speaker-Role Adaptation in Neural Conversation Models

    • [https://arxiv.org/abs/1710.07388]

  20. Chatbot Evaluation and Database Expansion via Crowdsourcing

    • [http://www.cs.cmu.edu/afs/cs/user/zhouyu/www/LREC.pdf]

  21. A Neural Network Approach for Knowledge-Driven Response Generation

    • [http://www.aclweb.org/anthology/C16-1318]

  22. Training End-to-End Dialogue Systems with the Ubuntu Dialogue Corpus

    • [http://www.cs.toronto.edu/~lcharlin/papers/ubuntu_dialogue_dd17.pdf\]

  23. Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memory  ACL 2017

    • [https://arxiv.org/abs/1704.01074]

  24. Flexible End-to-End Dialogue System for Knowledge Grounded Conversation

    • [https://arxiv.org/abs/1709.04264]

  25. Augmenting End-to-End Dialog Systems with Commonsense Knowledge

    • [https://arxiv.org/abs/1709.05453]

  26. Evaluating Prerequisite Qualities for Learning End-to-End Dialog Systems

    • [https://arxiv.org/abs/1511.06931]

  27. Attention with Intention for a Neural Network Conversation Model

    • [https://arxiv.org/abs/1510.08565]

  28. Response Selection with Topic Clues for Retrieval-based Chatbots

    • [https://arxiv.org/abs/1605.00090]

  29. LSTM based Conversation Models

    • [https://arxiv.org/abs/1603.09457]

  30. Not All Dialogues are Created Equal: Instance Weighting for Neural Conversational Models

    • [https://arxiv.org/abs/1704.08966]

  31. Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders   ACL 2017

    • [https://arxiv.org/abs/1703.10960]

  32. Words Or Characters? Fine-Grained Gating For Reading Comprehension    ACL 2017

    • [https://arxiv.org/abs/1611.01724v1]


综述

  1. The Dialog State Tracking Challenge Series: A Review

    • [https://www.microsoft.com/en-us/research/wp-content/uploads/2016/06/williams2016dstc_overview-1.pdf\]

  2. A Survey of Available Corpora for Building Data-Driven Dialogue Systems

    • [https://arxiv.org/abs/1512.05742]

  3. 任务型人机对话系统中的认知技术——— 概念、进展及其未来

    • [http://cjc.ict.ac.cn/online/cre/yk-2015112465445-20151210162142.pdf]


专门会议

  1. SIGDIAL ACL所属的关于对话系统的兴趣小组

    • [http://www.sigdial.org/workshops/conference18/]

  2. INTERSPEECH 2017: INTERSPEECH 2017 which will take place on August 21-24 in Stockholm, Sweden, after SIGDIAL

  3. YRRSDS 2017: Young Researchers’ Roundtable on Spoken Dialog Systems, which will take place on August 13-14 also in Saarbrücken, Germany, right before SIGDIAL.

  4. SemDial 2017!

    • [http://www.saardial.uni-saarland.de/]

  5. Dialog System Technology Challenge (DSTC)

    • [https://www.microsoft.com/en-us/research/event/dialog-state-tracking-challenge/]

    • [https://github.com/mesnilgr/is13]


Tutorial

  1. 2017 Tutorial - Deep Learning for Dialogue Systems  ACL 2017

    • [https://sites.google.com/site/deeplearningdialogue/]

  2. Research Blog: Computer, respond to this email.

    • [https://research.googleblog.com/2015/11/computer-respond-to-this-email.html]

  3. Deep Learning for Chatbots, Part 1 – Introduction

    • [http://www.wildml.com/2016/04/deep-learning-for-chatbots-part-1-introduction/]

  4. Deep Learning for Chatbots, Part 2 – Implementing a Retrieval-Based Model in Tensorflow

    • [http://www.wildml.com/2016/07/deep-learning-for-chatbots-2-retrieval-based-model-tensorflow/]

  5. Chatbot Fundamentals An interactive guide to writing bots in Python

    • [https://apps.worldwritable.com/tutorials/chatbot/]

  6. Chatbot Tutorial

    • [https://www.codeproject.com/Articles/36106/Chatbot-Tutorial#intro]


软件

Chatbot

  1. ParlAI A framework for training and evaluating AI models on a variety of openly available dialog datasets.

    • [https://github.com/facebookresearch/ParlAI]

  2. stanford-tensorflow-tutorials A neural chatbot using sequence to sequence model with attentional decoder.

    • [https://github.com/chiphuyen/stanford-tensorflow-tutorials/tree/master/assignments/chatbot]

  3. ChatterBot ChatterBot is a machine learning, conversational dialog engine for creating chat bots

    • [http://chatterbot.readthedocs.io/]

  4. DeepQA My tensorflow implementation of "A neural conversational model", a Deep learning based chatbot

    • [https://github.com/Conchylicultor/DeepQA]

  5. neuralconvo Neural conversational model in Torch

    • [https://github.com/macournoyer/neuralconvo]

  6. chatbot-rnn A toy chatbot powered by deep learning and trained on data from Reddit

    • [https://github.com/pender/chatbot-rnn]

  7. tf_seq2seq_chatbot tensorflow seq2seq chatbot

    • [https://github.com/nicolas-ivanov/tf_seq2seq_chatbot]

  8. ai-chatbot-framework A python chatbot framework with Natural Language Understanding and Artificial Intelligence.

    • [https://github.com/alfredfrancis/ai-chatbot-framework]

  9. DeepChatModels Conversation Models in Tensorflow

    • [https://github.com/mckinziebrandon/DeepChatModels]

  10. Chatbot Build your own chatbot base on IBM Watson

    • [https://webchatbot.mybluemix.net/]

  11. Chatbot An AI Based Chatbot

    • [http://chatbot.sohelamin.com/]

  12. neural-chatbot A chatbot based on seq2seq architecture done with tensorflow.

    • [https://github.com/inikdom/neural-chatbot]


Chinese_Chatbot

  1. Seq2Seq_Chatbot_QA 使用TensorFlow实现的Sequence to Sequence的聊天机器人模型

    • [https://github.com/qhduan/Seq2Seq_Chatbot_QA]

  2. Chatbot 基於向量匹配的情境式聊天機器人

    • [https://github.com/zake7749/Chatbot]

  3. chatbot-zh-torch7 中文Neural conversational model in Torch

    • [https://github.com/majoressense/chatbot-zh-torch7]


数据集

  1. Cornell Movie-Dialogs Corpus

    • [http://www.cs.cornell.edu/cristian/CornellMovie-DialogsCorpus.html]

  2. Dialog_Corpus Datasets for Training Chatbot System

    • [https://github.com/candlewill/Dialog_Corpus]

  3. OpenSubtitles A series of scripts to download and parse the OpenSubtitles corpus.

    • [https://github.com/AlJohri/OpenSubtitles]

  4. insuranceqa-corpus-zh OpenData in insurance area for Machine Learning Tasks

    • [https://github.com/Samurais/insuranceqa-corpus-zh]

  5. dgk_lost_conv dgk_lost_conv 中文对白语料 chinese conversation corpus

    • [https://github.com/majoressense/dgk_lost_conv]

  6. Frames: A Corpus for Adding Memory to Goal-Oriented Dialogue Systems 一共 1369 段对话，平均每段对话 15 轮。

    • [http://datasets.maluuba.com/Frames]

  7. Ubuntu Dialogue Corpus

    • [http://dataset.cs.mcgill.ca/ubuntu-corpus-1.0/]


领域专家

  1. Cambridge Dialogue Systems Group Steve Young

    • [http://mi.eng.cam.ac.uk/research/dialogue/]

  2. Ming Zhou

    • [https://www.microsoft.com/en-us/research/people/mingzhou/]

  3. Jiwei Li(李纪为), - [http://web.stanford.edu/jiweil/]

  4. Ryan Lowe, - [http://cs.mcgill.ca/rlowe1/]

  5. Lili Mou

    • [https://lili-mou.github.io/]

  6. Jason Williams Microsoft

    • [https://www.microsoft.com/en-us/research/people/jawillia/]

  7. Bing Liu (刘冰) CMU

    • [http://bingliu.me/]

  8. Ian Lane

    • [http://www.cs.cmu.edu/~ianlane/#&panel1-1]

  9. Ondřej Dušek

    • https://ufal.mff.cuni.cz/ondrej-dusek

  10. Sungjin Lee 微软

    • [https://www.microsoft.com/en-us/research/people/sule/]

  11. Zhou Yu   俞舟 CMU

    • [http://www.cs.cmu.edu/~zhouyu/]

  12. 华为诺亚实验室

    • [http://www.noahlab.com.hk/topics/ShortTextConversation]

  13. 刘挺 哈尔滨工业大学

    • [http://ir.hit.edu.cn/~tliu]

  14. 张伟男 哈尔滨工业大学  - [http://ir.hit.edu.cn/~wnzhang]

  15. Wei Wu (武威) 微软

    • [https://www.microsoft.com/en-us/research/people/wuwei/]

  16. 赵军 中科院自动化所

    • [http://www.nlpr.ia.ac.cn/cip/jzhao.htm]

  17. 黄民烈 清华

    • [http://aihuang.org/p/]



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