Generating and Validating Contextually Relevant Justifications for Conversational Recommendation

Author:

Volokhin Sergey1,Collins Marcus2,Rokhlenko Oleg2,Agichtein Eugene1

Affiliation:

1. Emory University, United States

2. Amazon, United States

Publisher

ACM

Reference28 articles.

1. Measuring Recommendation Explanation Quality

2. Florian Boudin . 2016 . PKE: an open source python-based keyphrase extraction toolkit . In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations . Osaka, Japan, 69–73. http://aclweb.org/anthology/C16- 2015 Florian Boudin. 2016. PKE: an open source python-based keyphrase extraction toolkit. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations. Osaka, Japan, 69–73. http://aclweb.org/anthology/C16-2015

3. Daniel Cer Yinfei Yang Sheng-yi Kong Nan Hua Nicole Limtiaco Rhomni St John Noah Constant Mario Guajardo-Cespedes Steve Yuan Chris Tar 2018. Universal sentence encoder. arXiv preprint arXiv:1803.11175(2018). Daniel Cer Yinfei Yang Sheng-yi Kong Nan Hua Nicole Limtiaco Rhomni St John Noah Constant Mario Guajardo-Cespedes Steve Yuan Chris Tar 2018. Universal sentence encoder. arXiv preprint arXiv:1803.11175(2018).

4. Learning to Rank Features for Recommendation over Multiple Categories

5. Automatic Generation of Natural Language Explanations

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Introducing contextual transparency for automated decision systems;Nature Machine Intelligence;2023-03-13

2. Conversational Information Seeking;Foundations and Trends® in Information Retrieval;2023

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