Abstract
Current information exploration models present low-level features or technical aspects related to the paradigm used to generate results. While this may increase transparency, it does not help the user form a personal opinion about items because it does not describe the overall experience with them. In order to address this issue, we propose the INTERactivE viSualizaTion model (INTEREST) that supports the exploration and analysis of search results by means of a graphical representation of consumer feedback aimed at making the user aware of the service properties in all the stages of fruition, focusing on the data that is most relevant to her/him. INTEREST is based on the Service Journey Maps for the design and description of user experience with services. We applied it to the home booking domain by developing the Apartment Monitoring application that supports overviewing and analyzing online reviews about rented homes. In a user study, we compared the decision-making support provided by our application with that of a baseline model that enables a temporal filtering of consumer feedback. We found out that Apartment Monitoring outperforms the baseline in user experience, user awareness of item properties, and user control during the interaction with the system. In particular, according to the participants of the study, Apartment Monitoring describes the expectations about the homes and it supports their selection in a more effective way than the baseline. These findings encourage moving from a low-level description of item properties to a service-oriented one in order to improve users’ decision-making capabilities.
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
4 articles.
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1. Justification of recommender systems results: a service-based approach;User Modeling and User-Adapted Interaction;2022-10-29
2. Service-aware Recommendation and Justification of Results;Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization;2022-07-04
3. Service-Aware Personalized Item Recommendation;IEEE Access;2022
4. User and item-aware estimation of review helpfulness;Information Processing & Management;2021-01