Mr Yaxiong Wu

  • Tutor (School of Computing Science)

Publications

List by: Type | Date

Jump to: 2022 | 2021 | 2020
Number of items: 5.

2022

Wu, Y., Macdonald, C. and Ounis, I. (2022) Multi-Modal Dialog State Tracking for Interactive Fashion Recommendation. In: ACM Conference on Recommender Systems (RecSys 2022), Seattle, USA, 18-23 Sep 2022, (Accepted for Publication)

Wu, Y., Macdonald, C. and Ounis, I. (2022) Multimodal Conversational Fashion Recommendation with Positive and Negative Natural-Language Feedback. In: CUI 2022, Glasgow, UK, 26-28 Jul 2022, (Accepted for Publication)

2021

Wu, Y., Macdonald, C. and Ounis, I. (2021) Partially Observable Reinforcement Learning for Dialog-based Interactive Recommendation. In: 15th ACM Conference on Recommender Systems (RecSys21), Amsterdam, The Netherlands, 27 Sep - 01 Oct 2021, pp. 241-251. (doi: 10.1145/3460231.3474256)

2020

Meng, Z. et al. (2020) BETA-Rec: Build, Evaluate and Tune Automated Recommender Systems. In: 14th ACM Conference on Recommender Systems (RecSys 2020), 22-26 Sep 2020, pp. 588-590. ISBN 9781450375832 (doi: 10.1145/3383313.3411524)

Wu, Y., Macdonald, C. and Ounis, I. (2020) A Hybrid Conditional Variational Autoencoder Model for Personalised Top-n Recommendation. In: ICTIR 2020: The 6th ACM International Conference on the Theory of Information Retrieval, Stavanger, Norway, 14-18 Sep 2020, pp. 89-96. ISBN 9781450380676 (doi: 10.1145/3409256.3409835)

This list was generated on Wed Jun 29 19:46:02 2022 BST.
Number of items: 5.

Conference Proceedings

Wu, Y., Macdonald, C. and Ounis, I. (2022) Multi-Modal Dialog State Tracking for Interactive Fashion Recommendation. In: ACM Conference on Recommender Systems (RecSys 2022), Seattle, USA, 18-23 Sep 2022, (Accepted for Publication)

Wu, Y., Macdonald, C. and Ounis, I. (2022) Multimodal Conversational Fashion Recommendation with Positive and Negative Natural-Language Feedback. In: CUI 2022, Glasgow, UK, 26-28 Jul 2022, (Accepted for Publication)

Wu, Y., Macdonald, C. and Ounis, I. (2021) Partially Observable Reinforcement Learning for Dialog-based Interactive Recommendation. In: 15th ACM Conference on Recommender Systems (RecSys21), Amsterdam, The Netherlands, 27 Sep - 01 Oct 2021, pp. 241-251. (doi: 10.1145/3460231.3474256)

Meng, Z. et al. (2020) BETA-Rec: Build, Evaluate and Tune Automated Recommender Systems. In: 14th ACM Conference on Recommender Systems (RecSys 2020), 22-26 Sep 2020, pp. 588-590. ISBN 9781450375832 (doi: 10.1145/3383313.3411524)

Wu, Y., Macdonald, C. and Ounis, I. (2020) A Hybrid Conditional Variational Autoencoder Model for Personalised Top-n Recommendation. In: ICTIR 2020: The 6th ACM International Conference on the Theory of Information Retrieval, Stavanger, Norway, 14-18 Sep 2020, pp. 89-96. ISBN 9781450380676 (doi: 10.1145/3409256.3409835)

This list was generated on Wed Jun 29 19:46:02 2022 BST.

Research datasets

Jump to: 2020
Number of items: 1.

2020

Wu, Y., Macdonald, C. and Ounis, I. (2020) A Hybrid Conditional Variational Autoencoder Model for Personalised Top-N Recommendation. [Data Collection]

This list was generated on Wed Jun 29 19:46:03 2022 BST.