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2025 | OriginalPaper | Chapter

AUTO-DataGenCARS+: An Advanced User-Oriented Tool to Generate Data for the Evaluation of Recommender Systems

Authors : María del Carmen Rodríguez-Hernández, Sergio Ilarri, Marcos Caballero, Raquel Trillo-Lado, Ramón Hermoso, Rafael del-Hoyo-Alonso

Published in: Advances in Mobile Computing and Multimedia Intelligence

Publisher: Springer Nature Switzerland

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Abstract

Context-Aware Recommender Systems (CARS) offer context-based suggestions that are particularly crucial in the tourism domain, where personalized experiences significantly enhance user satisfaction. However, the evaluation of CARS is a challenge, partly due to the scarce availability of appropriate datasets that fulfill a variety of evaluation purposes. For example, to evaluate CARS, we need datasets that incorporate context data, but in practice existing datasets provide very little contextual information.
This paper presents AUTO-DataGenCARS+, a graphical user-oriented tool designed to generate synthetic data for evaluating both Recommender Systems and CARS. Some of the relevant features of the tool include: a flexible definition of user profiles, user, item and context schemas; a realistic generation of ratings and item attributes; the possibility to mix real and synthetic datasets; functionalities for analyzing and evaluating existing datasets; and an extendable architecture for advanced users. We illustrate the benefits of AUTO-DataGenCARS+ through several examples and experimental evaluations.

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Metadata
Title
AUTO-DataGenCARS+: An Advanced User-Oriented Tool to Generate Data for the Evaluation of Recommender Systems
Authors
María del Carmen Rodríguez-Hernández
Sergio Ilarri
Marcos Caballero
Raquel Trillo-Lado
Ramón Hermoso
Rafael del-Hoyo-Alonso
Copyright Year
2025
Book
Advances in Mobile Computing and Multimedia Intelligence

Print ISBN: 978-3-031-78048-6

Electronic ISBN: 978-3-031-78049-3

Copyright Year: 2025

DOI
https://doi.org/10.1007/978-3-031-78049-3_16

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