Toward Tone-Aware Explanations in Recommender Systems

Author:

Okoso Ayano1ORCID,Otaki Keisuke1ORCID,Koide Satoshi2ORCID,Baba Yukino3ORCID

Affiliation:

1. Collaborative Intelligence Research-Domain, Toyota Central R&D Labs., Inc., Japan

2. Toyota Central Research and Development Lab., Japan

3. Graduate School of Arts and Sciences, University of Tokyo, Japan

Publisher

ACM

Reference43 articles.

1. Douglas Biber and Susan Conrad. 2019. Register, genre, and style. Cambridge University Press.

2. Nancy Bonvillain. 2019. Language culture and communication: The meaning of messages. Rowman & Littlefield.

3. Shuo Chang F Maxwell Harper and Loren Gilbert Terveen. 2016. Crowd-based personalized natural language explanations for recommendations. In RecSys. ACM 175–182.

4. Dan Cosley, Shyong K Lam, Istvan Albert, Joseph A Konstan, and John Riedl. 2003. Is seeing believing? How recommender system interfaces affect users’ opinions. In SIGCHI. ACM, 585–592.

5. Henriette Cramer, Vanessa Evers, Satyan Ramlal, Maarten Van Someren, Lloyd Rutledge, Natalia Stash, Lora Aroyo, and Bob Wielinga. 2008. The effects of transparency on trust in and acceptance of a content-based art recommender. UMUAI (2008), 455–496.

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