Service-based Presentation of Multimodal Information for the Justification of Recommender Systems Results

Zhongli Filippo Hu, Noemi Mauro, Giovanna Petrone, Liliana Ardissono

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.