Knowledge-guided Deep Reinforcement Learning for Interactive Recommendation

2020 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn48605.2020.9207010 ◽

2020 ◽

Author(s):

Xiaocong Chen ◽

Chaoran Huang ◽

Lina Yao ◽

Xianzhi Wang ◽

Wei liu ◽

...

Keyword(s):

Reinforcement Learning ◽

Interactive Recommendation

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Partially Observable Reinforcement Learning for Dialog-based Interactive Recommendation

10.1145/3460231.3474256 ◽

2021 ◽

Author(s):

Yaxiong Wu ◽

Craig Macdonald ◽

Iadh Ounis

Keyword(s):

Reinforcement Learning ◽

Partially Observable ◽

Interactive Recommendation

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Research on interactive recommendation system based on reinforcement learning

10.1117/12.2624858 ◽

2021 ◽

Author(s):

Qifan Wang ◽

Hongwei Shi

Keyword(s):

Reinforcement Learning ◽

Recommendation System ◽

Interactive Recommendation

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A Reinforcement Learning Approach to Achieve Unobtrusive and Interactive Recommendation Systems for Web-Based Communities

Lecture Notes in Computer Science - Adaptive Hypermedia and Adaptive Web-Based Systems ◽

10.1007/978-3-540-27780-4_62 ◽

2004 ◽

pp. 409-412 ◽

Author(s):

Felix Hernandez ◽

Elena Gaudioso ◽

Jesús G. Boticario

Keyword(s):

Reinforcement Learning ◽

Recommendation Systems ◽

Learning Approach ◽

Web Based ◽

Interactive Recommendation

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Interactive Recommendation with User-Specific Deep Reinforcement Learning

ACM Transactions on Knowledge Discovery from Data ◽

10.1145/3359554 ◽

2019 ◽

Vol 13 (6) ◽

pp. 1-15

Author(s):

Yu Lei ◽

Wenjie Li

Keyword(s):

Reinforcement Learning ◽

Interactive Recommendation

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Balancing Between Accuracy and Fairness for Interactive Recommendation with Reinforcement Learning

Advances in Knowledge Discovery and Data Mining - Lecture Notes in Computer Science ◽

10.1007/978-3-030-47426-3_13 ◽

2020 ◽

pp. 155-167

Author(s):

Weiwen Liu ◽

Feng Liu ◽

Ruiming Tang ◽

Ben Liao ◽

Guangyong Chen ◽

...

Keyword(s):

Reinforcement Learning ◽

Interactive Recommendation

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Improving ranking function and diversification in interactive recommendation systems based on deep reinforcement learning

2021 26th International Computer Conference, Computer Society of Iran (CSICC) ◽

10.1109/csicc52343.2021.9420615 ◽

2021 ◽

Author(s):

Vahid Baghi ◽

Seyed Mohammad Seyed Motehayeri ◽

Ali Moeini ◽

Rooholah Abedian

Keyword(s):

Reinforcement Learning ◽

Recommendation Systems ◽

Ranking Function ◽

Interactive Recommendation

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Large-scale Interactive Recommendation with Tree-structured Reinforcement Learning

IEEE Transactions on Knowledge and Data Engineering ◽

10.1109/tkde.2021.3137310 ◽

2021 ◽

pp. 1-1

Author(s):

Haokun Chen ◽

Chenxu Zhu ◽

Ruiming Tang ◽

Weinan Zhang ◽

Xiuqiang He ◽

...

Keyword(s):

Reinforcement Learning ◽

Large Scale ◽

Interactive Recommendation

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DRCGR: Deep Reinforcement Learning Framework Incorporating CNN and GAN-Based for Interactive Recommendation

2019 IEEE International Conference on Data Mining (ICDM) ◽

10.1109/icdm.2019.00122 ◽

2019 ◽

Author(s):

Rong Gao ◽

Haifeng Xia ◽

Jing Li ◽

Donghua Liu ◽

Shuai Chen ◽

...

Keyword(s):

Reinforcement Learning ◽

Learning Framework ◽

Interactive Recommendation

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Supplemental Material for Reconciling Reinforcement Learning Models With Behavioral Extinction and Renewal: Implications for Addiction, Relapse, and Problem Gambling

Psychological Review ◽

10.1037/0033-295x.114.3.784.supp ◽

2007 ◽

Keyword(s):

Reinforcement Learning ◽

Problem Gambling ◽

Learning Models ◽

Behavioral Extinction ◽

Reinforcement Learning Models

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Bayes factors for reinforcement-learning models of the Iowa gambling task.

Decision ◽

10.1037/dec0000040 ◽

2016 ◽

Vol 3 (2) ◽

pp. 115-131 ◽

Author(s):

Helen Steingroever ◽

Ruud Wetzels ◽

Eric-Jan Wagenmakers

Keyword(s):

Reinforcement Learning ◽

Iowa Gambling Task ◽

Bayes Factors ◽

Gambling Task ◽

Learning Models ◽

Reinforcement Learning Models

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