%0 Conference Paper %1 Hu_2023 %A Hu, Zhongli Filippo %A Mauro, Noemi %A Petrone, Giovanna %A Ardissono, Liliana %B Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization %D 2023 %I ACM %K explanation multi-stakeholder recommender umap2023 %P 46-53 %R 10.1145/3565472.3592962 %T Service-based Presentation of Multimodal Information for the Justification of Recommender Systems Results %U https://doi.org/10.1145%2F3565472.3592962 %X The current models for the explanation and justification of recommender systems results focus on qualitative and quantitative data about items, overlooking the power of images to describe the different aspects of experience that the consumer should expect from their selection to post-sales. In the present paper, we extend previous justification models by exploiting object recognition on images to support a service-oriented presentation of multimodal (textual, quantitative, and images) information about items. As a testbed for our model, we chose the home-booking domain. In a user study, we found that item comparison can be enhanced by empowering the user to filter multimodal data based on a set of evaluation dimensions describing the experience with items. These results encourage the introduction of service-based filters for multimodal information retrieval in product and service catalogs.

@inproceedings{Hu_2023, abstract = {The current models for the explanation and justification of recommender systems results focus on qualitative and quantitative data about items, overlooking the power of images to describe the different aspects of experience that the consumer should expect from their selection to post-sales. In the present paper, we extend previous justification models by exploiting object recognition on images to support a service-oriented presentation of multimodal (textual, quantitative, and images) information about items. As a testbed for our model, we chose the home-booking domain. In a user study, we found that item comparison can be enhanced by empowering the user to filter multimodal data based on a set of evaluation dimensions describing the experience with items. These results encourage the introduction of service-based filters for multimodal information retrieval in product and service catalogs.}, added-at = {2023-06-29T15:36:30.000+0200}, author = {Hu, Zhongli Filippo and Mauro, Noemi and Petrone, Giovanna and Ardissono, Liliana}, biburl = {https://www.bibsonomy.org/bibtex/21cf691f45cfa98b2cd61b427edfbc86c/brusilovsky}, booktitle = {Proceedings of the 31st {ACM} Conference on User Modeling, Adaptation and Personalization}, description = {Service-based Presentation of Multimodal Information for the Justification of Recommender Systems Results | Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization}, doi = {10.1145/3565472.3592962}, interhash = {87de4b8730804931b523e339f0bcdde8}, intrahash = {1cf691f45cfa98b2cd61b427edfbc86c}, keywords = {explanation multi-stakeholder recommender umap2023}, month = jun, pages = {46-53}, publisher = {{ACM}}, timestamp = {2023-06-29T15:36:30.000+0200}, title = {Service-based Presentation of Multimodal Information for the Justification of Recommender Systems Results}, url = {https://doi.org/10.1145%2F3565472.3592962}, year = 2023 }