Looks Can Be Deceiving: Linking User-Item Interactions and User's Propensity Towards Multi-Objective Recommendations

July 02, 2023 Β· Declared Dead Β· πŸ› ACM Conference on Recommender Systems

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Authors Patrik Dokoupil, Ladislav Peska, Ludovico Boratto arXiv ID 2307.00654 Category cs.IR: Information Retrieval Citations 7 Venue ACM Conference on Recommender Systems Last Checked 4 months ago
Abstract
Multi-objective recommender systems (MORS) provide suggestions to users according to multiple (and possibly conflicting) goals. When a system optimizes its results at the individual-user level, it tailors them on a user's propensity towards the different objectives. Hence, the capability to understand users' fine-grained needs towards each goal is crucial. In this paper, we present the results of a user study in which we monitored the way users interacted with recommended items, as well as their self-proclaimed propensities towards relevance, novelty and diversity objectives. The study was divided into several sessions, where users evaluated recommendation lists originating from a relevance-only single-objective baseline as well as MORS. We show that despite MORS-based recommendations attracted less selections, its presence in the early sessions is crucial for users' satisfaction in the later stages. Surprisingly, the self-proclaimed willingness of users to interact with novel and diverse items is not always reflected in the recommendations they accept. Post-study questionnaires provide insights on how to deal with this matter, suggesting that MORS-based results should be accompanied by elements that allow users to understand the recommendations, so as to facilitate their acceptance.
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