On-demand Personalized Explanation for Transparent Recommendation-Reference-Cited by-同舟云学术

On-demand Personalized Explanation for Transparent Recommendation

Published:2021-06-21 Issue: Volume: Page:
ISSN:
Container-title:Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization
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Author:

Guesmi Mouadh¹,Chatti Mohamed Amine¹,Vorgerd Laura¹,Joarder Shoeb¹,Zumor Shadi¹,Sun Yiqi²,Ji Fangzheng³,Muslim Arham⁴

Affiliation:

1. University of Duisburg-Essen, Germany

2. University of Duisburg Essen, Germany

3. University of Duisburg, Germany

4. National University of Sciences and Technology, Pakistan

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3450614.3464479

Reference23 articles.

1. Vijay Arya Rachel KE Bellamy Pin-Yu Chen Amit Dhurandhar Michael Hind Samuel C Hoffman Stephanie Houde Q Vera Liao Ronny Luss Aleksandra Mojsilović 2019. One explanation does not fit all: A toolkit and taxonomy of ai explainability techniques. arXiv preprint arXiv:1909.03012(2019). Vijay Arya Rachel KE Bellamy Pin-Yu Chen Amit Dhurandhar Michael Hind Samuel C Hoffman Stephanie Houde Q Vera Liao Ronny Luss Aleksandra Mojsilović 2019. One explanation does not fit all: A toolkit and taxonomy of ai explainability techniques. arXiv preprint arXiv:1909.03012(2019).

2. Crowd-Based Personalized Natural Language Explanations for Recommendations

3. What Is Personalization? Perspectives on the Design and Implementation of Personalization in Information Systems

4. How should I explain? A comparison of different explanation types for recommender systems

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