Work

Dynamic Personalization of Multimedia Content Based on User Model

Year: 2024

Type: conference-paper

Abstract: This project investigates the potential of personalized interactions with social robots, like Pepper, by customizing images and videos to align with individual user profiles. The primary goal is to make conversations with social robots more engaging and relatable. By tailoring content to factors such as age, gender, interests, and cultural background, we aim to enhance user satisfaction and foster broader acceptance of social robots in everyday settings. This study opens up new possibilities for designing robots that can adapt to diverse user needs and preferences. Ultimately, this approach could lead to social robots that are more widely accepted and valued in a range of contexts, from customer service to education to healthcare. This project provides a path for future research in context-aware robot communication.

Source: ACM Conference on User Modeling, Adaptation and Personalization (UMAP)

DOI: 10.1145/3631700.3664889

Authors: Massimo Donini, Cristina Gena, Alessandro Mazzei, Irene Borgini, Matteo Nazzario

Institutions: University of Turin, Intesa Sanpaolo (Italy), Intesa Sanpaolo Innovation Center (Italy)

Language: English

Topic: Social Robot Interaction and HRI

Subfield: Social Psychology

Field: Psychology

Domain: Social Sciences

Open Access status: hybrid

OpenAlex ID: W4400106318

FWCI: 1.247

Cites: 18

Cited by: 3

Related to: 10