Generating Natural Language Explanations for Group Recommendations in High Divergence Scenarios

Generating Natural Language Explanations for Group Recommendations in High Divergence Scenarios

Najafian, S. (TU Delft Web Information Systems)

2020

In some scenarios, like music or tourism, people often consume items in groups. However, reaching a consensus is difficult as different members of the group may have highly diverging tastes. To keep the rest of the group satisfied, an individual might need to be confronted occasionally with items they do not like. In this context, presenting an explanation of how the system came up with the recommended item(s), may make it easier for users to accept items they might not like for the benefit of the group. This paper presents our progress on proposing improved algorithms for recommending items (for both music and tourism) for a group to consume and an approach for generating natural language explanations. Our future directions include extending the current work by modelling different factors that we need to consider when we generate explanations for groups e.g. size of the group, group members' personality, demographics, and their relationship.

Explanations
Group recommendations
Human-centered computing user studies
Preference aggregation strategies

http://resolver.tudelft.nl/uuid:e0c9cac6-a371-413f-87f8-0c62c7941d03

https://doi.org/10.1145/3379336.3381512

9781450375139

Proceedings of the 25th International Conference on Intelligent User Interfaces Companion. IUI 2020

25th ACM International Conference on Intelligent User Interfaces, IUI 2020, 2020-03-17 → 2020-03-20, Cagliari, Italy

Institutional Repository

conference paper

© 2020 S. Najafian