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In this paper, we propose a novel end-to-end framework called KBRD, which stands for Knowledge-Based Recommender Dialog System.
Towards knowledge-based personalized product description generation in e-commerce
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Deep conversational recommender in travel
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Grouplens: An open architecture for collaborative filtering of netnews
Paul Resnick, Neophytos Iacovou, Mitesh Suchak, Peter Bergstrom, and John Riedl. 1994 · 1994
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Item-based collaborative filtering recommendation algorithms
Badrul Sarwar, George Karypis, Joseph Konstan, and John Riedl. 2001 · 2001
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Methods and metrics for cold-start recommendations
Andrew I Schein, Alexandrin Popescul, Lyle H Ungar, and David M Pennock. 2002 · 2002
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A personalized system for conversational recommendations
Cynthia A Thompson, Mehmet H Goker, and Pat Langley. 2004 · 2004
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Improving recommender systems with adaptive conversational strategies
Tariq Mahmood and Francesco Ricci. 2009 · 2009
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A matrix factorization technique with trust propagation for recommendation in social networks
Mohsen Jamali and Martin Ester. 2010 · 2010
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Critiquing-based recommenders: survey and emerging trends
Li Chen and Pearl Pu. 2012 · 2012
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Improving efficiency and accuracy in multilingual entity extraction
Joachim Daiber, Max Jakob, Chris Hokamp, and Pablo N Mendes. 2013 · 2013
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V. Le. 2014 · 2014
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A framework of conversational recommender system based on user functional requirements
Dwi H Widyantoro and ZKA Baizal. 2014 · 2014
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Personalized entity recommendation: A heterogeneous information network approach
Xiao Yu, Xiang Ren, Yizhou Sun, Quanquan Gu, Bradley Sturt, Urvashi Khandelwal, Brandon Norick, and Jiawei Han. 2014 · 2014
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Explicit factor models for explainable recommendation based on phrase-level sentiment analysis
Yongfeng Zhang, Guokun Lai, Min Zhang, Yi Zhang, Yiqun Liu, and Shaoping Ma. 2014 · 2014
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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Dbpedia–a large-scale, multilingual knowledge base extracted from wikipedia
Jens Lehmann, Robert Isele, Max Jakob, Anja Jentzsch, Dimitris Kontokostas, Pablo N Mendes, Sebastian Hellmann, Mohamed Morsey, Patrick Van Kleef, Sören Auer, et al. 2015 · 2015
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Autorec: Autoencoders meet collaborative filtering
Suvash Sedhain, Aditya Krishna Menon, Scott Sanner, and Lexing Xie. 2015 · 2015
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A hierarchical recurrent encoder-decoder for generative context-aware query suggestion
Alessandro Sordoni, Yoshua Bengio, Hossein Vahabi, Christina Lioma, Jakob Grue Simonsen, and Jian-Yun Nie. 2015a · 2015
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A neural network approach to context-sensitive generation of conversational responses
Alessandro Sordoni, Michel Galley, Michael Auli, Chris Brockett, Yangfeng Ji, Margaret Mitchell, Jian-Yun Nie, Jianfeng Gao, and Bill Dolan. 2015b · 2015
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Oriol Vinyals and Quoc Le. 2015 · 2015
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Guesswhat?! visual object discovery through multi-modal dialogue
Harm De Vries, Florian Strub, Sarath Chandar, Olivier Pietquin, Hugo Larochelle, and Aaron Courville. 2017 · 2017
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Neural collaborative filtering
Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, and Tat-Seng Chua. 2017 · 2017
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A structured self-attentive sentence embedding
Zhouhan Lin, Minwei Feng, Cícero Nogueira dos Santos, Mo Yu, Bing Xiang, Bowen Zhou, and Yoshua Bengio. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Towards deep conversational recommendations
Raymond Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, and Chris Pal. 2018 · 2018
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Generating wikipedia by summarizing long sequences
Peter J. Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, and Noam Shazeer. 2018 · 2018
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Collaborative deep learning for recommender systems
Hao Wang, Naiyan Wang, and Dit-Yan Yeung. 2015 · 2015
Cited alongside, same era.
Semantically conditioned lstm-based natural language generation for spoken dialogue systems
Tsung-Hsien Wen, Milica Gasic, Nikola Mrkšić, Pei-Hao Su, David Vandyke, and Steve Young. 2015 · 2015
Cited alongside, same era.
Towards conversational recommender systems
Konstantina Christakopoulou, Filip Radlinski, and Katja Hofmann. 2016 · 2016
Cited alongside, same era.
Evaluating prerequisite qualities for learning end-to-end dialog systems
Jesse Dodge, Andreea Gane, Xiang Zhang, Antoine Bordes, Sumit Chopra, Alexander H. Miller, Arthur Szlam, and Jason Weston. 2016 · 2016
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Pointing the unknown words
Caglar Gulcehre, Sungjin Ahn, Ramesh Nallapati, Bowen Zhou, and Yoshua Bengio. 2016 · 2016
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Squad: 100, 000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Building end-to-end dialogue systems using generative hierarchical neural network models
Iulian Vlad Serban, Alessandro Sordoni, Yoshua Bengio, Aaron C. Courville, and Joelle Pineau. 2016 · 2016
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Extreme adaptation for personalized neural machine translation
Paul Michel and Graham Neubig. 2018 · 2018
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Scaling neural machine translation
Myle Ott, Sergey Edunov, David Grangier, and Michael Auli. 2018 · 2018
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Modeling relational data with graph convolutional networks
Michael Schlichtkrull, Thomas N Kipf, Peter Bloem, Rianne Van Den Berg, Ivan Titov, and Max Welling. 2018 · 2018
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Conversational recommender system
Yueming Sun and Yi Zhang. 2018 · 2018
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A reinforcement learning framework for explainable recommendation
Xiting Wang, Yiru Chen, Jie Yang, Le Wu, Zhengtao Wu, and Xing Xie. 2018b · 2018
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Hotpotqa: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W. Cohen, Ruslan Salakhutdinov, and Christopher D. Manning. 2018 · 2018
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Graph convolutional neural networks for web-scale recommender systems
Rex Ying, Ruining He, Kaifeng Chen, Pong Eksombatchai, William L Hamilton, and Jure Leskovec. 2018 · 2018
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Explainable recommendation: A survey and new perspectives
Yongfeng Zhang and Xu Chen. 2018 · 2018
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Cognitive graph for multi-hop reading comprehension at scale
Ming Ding, Chang Zhou, Qibin Chen, Hongxia Yang, and Jie Tang. 2019 · 2019
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