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

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A10468878" target="_blank" >RIV/00216208:11320/23:10468878 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1145/3604915.3608848" target="_blank" >https://doi.org/10.1145/3604915.3608848</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3604915.3608848" target="_blank" >10.1145/3604915.3608848</a>

Result language

angličtina

Original language name

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

Original language description

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&apos;s propensity towards the different objectives. Hence, the capability to understand users&apos; 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 attracting fewer selections, their presence in the early sessions are crucial for users&apos; 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 the choice of whether a recommendation should be accepted or not. Detailed study results are available at https://bit.ly/looks-can-be-deceiving-repo.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GA22-21696S" target="_blank" >GA22-21696S: Deep Visual Representations of Unstructured Data</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 17th ACM Conference on Recommender Systems

ISBN

979-8-4007-0241-9

ISSN

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e-ISSN

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Number of pages

7

Pages from-to

912-918

Publisher name

ACM

Place of publication

New York, NY, USA

Event location

Singapore, Singapore

Event date

Sep 18, 2023

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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