The explanation and justification of recommender systems' results are challenging research tasks. On the one hand, a model-based description that clarifies the reasoning approach behind the suggestions might be difficult to understand, or it might fail to convince the user, if (s)he does not agree on the applied inference mechanism. On the other hand, an aspect-based justification based on few characteristics might provide a partial view of items or, if more detailed, it might overload the user with too much information. In order to address these issues, we propose a visual model aimed at justifying recommendations from a holistic perspective. Our model is based on a service-oriented summary of consumers' experience with items. We use the Service Journey Maps to extract data about the experience with services from online reviews, and to generate a visual summary of such feedback, based on evaluation dimensions that refer to all the stages of service fruition. Thanks to a graphical representation of these dimensions (based on bar graphs), and on the provision of on-demand data about the associated aspects of items, our model enables the user to overview the recommendation list and to quickly identify the subset of results that deserve to be inspected in detail for a final selection decision. A preliminary user study, based on the Apartment Monitoring application, has provided encouraging results about the usefulness and efficacy of our model to enhance user awareness and decision-making in the presence of medium-size recommendation lists.

A Service-oriented Perspective on the Summarization of Recommendations: Preliminary Experiment

Noemi Mauro;Zhongli Filippo Hu;Liliana Ardissono;Gianmarco Izzi
2021

Abstract

The explanation and justification of recommender systems' results are challenging research tasks. On the one hand, a model-based description that clarifies the reasoning approach behind the suggestions might be difficult to understand, or it might fail to convince the user, if (s)he does not agree on the applied inference mechanism. On the other hand, an aspect-based justification based on few characteristics might provide a partial view of items or, if more detailed, it might overload the user with too much information. In order to address these issues, we propose a visual model aimed at justifying recommendations from a holistic perspective. Our model is based on a service-oriented summary of consumers' experience with items. We use the Service Journey Maps to extract data about the experience with services from online reviews, and to generate a visual summary of such feedback, based on evaluation dimensions that refer to all the stages of service fruition. Thanks to a graphical representation of these dimensions (based on bar graphs), and on the provision of on-demand data about the associated aspects of items, our model enables the user to overview the recommendation list and to quickly identify the subset of results that deserve to be inspected in detail for a final selection decision. A preliminary user study, based on the Apartment Monitoring application, has provided encouraging results about the usefulness and efficacy of our model to enhance user awareness and decision-making in the presence of medium-size recommendation lists.
Explainable User Models and Personalized Systems (ExUM '21)
Utrecht, The Netherlands
21-25 June 2021
Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization (UMAP '21 Adjunct)
ACM
213
219
978-1-4503-8367-7
https://dl.acm.org/doi/10.1145/3450614.3464475
review-based recommender systems, summarization of recommendation lists, justification or results, Service Journey Maps
Noemi Mauro, Zhongli Filippo Hu, Liliana Ardissono, Gianmarco Izzi
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/1788454
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