Last update: October 2023
AUTO-DataGenCARS: Advanced User orienTed tOol DataGenCARS
Brief description
AUTO-DataGenCARS is a powerful graphical user interface that can be used to generate synthetic data for the evaluation of Recommender Systems (RS) and Context-Aware Recommender Systems (CARS). It extends our previous tool DataGenCARS with a flexible and useful GUI, user facilities, and new functionalities like the possibility to define, store, and import workflows and projects.
This invention has been registered in Spain (University of Zaragoza — PII-2021-0019).
IMPORTANT: this web page focuses on AUTO-DataGenCARS, which has been implemented in Java. We have recently developed a more advanced and new version of the tool in Python, which we call AUTO-DataGenCARS+, and which will be described soon in another webpage.
Documentation
Software
Resources
- To facilitate reproducibility and help to test the use cases, we provide some supporting files that could be used for each of the three examples of use cases included in the
Use case scenarios
; document:
Videos
- Some videos showing how to execute the examples described in the
Use case scenarios
; document — Java version:
Main Related Publications
María del Carmen Rodríguez-Hernández, Sergio Ilarri, Ramón Hermoso, Raquel Trillo-Lado, "DataGenCARS: A Generator of Synthetic Data for the Evaluation of Context-Aware Recommendation Systems", Pervasive and Mobile Computing, ISSN 1574-1192, volume 38, part 2, pp. 516-541, Elsevier, July 2017. Special Issue on Context-aware Mobile Recommender Systems.
(DOI: 10.1016/j.pmcj.2016.09.020)
María del Carmen Rodríguez-Hernández, Sergio Ilarri, Raquel Trillo-Lado, Ramón Hermoso,
"Context-Aware Recommendations Using Mobile P2P",
15th International Conference on Advances in Mobile Computing & Multimedia (MoMM 2017), Salzburg (Austria),
ACM Press, ISBN 978-1-4503-5300-7, pp. 82-91, December 2017.
(DOI: 10.1145/3151848.3151856)
María del Carmen Rodríguez-Hernández, Sergio Ilarri, Ramón Hermoso, Raquel Trillo-Lado,
"Towards Trajectory-Based Recommendations in Museums: Evaluation of Strategies Using Mixed Synthetic and Real Data", Eighth International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN 2017), Lund (Sweden), Elsevier, Procedia Computer Science, ISSN 1877-0509, volume 113, pp. 234-239, September 2017.
(DOI: 10.1016/j.procs.2017.08.355)
Contributors
Researchers
Students (final degree projects)
Acknowledgments
- Project PID2020-113037RB-I00 / AEI / 10.13039/501100011033 — Next-gEnerATion dAta Management to foster suitable Behaviors and the resilience of cItizens against modErN ChallEnges (NEAT-AMBIENCE).
- Government of Aragon (COSMOS research group; last group reference: T64_23R; previous group reference: T64_20R)
- Previous projects: Government of Aragon — Aquitaine-Aragon project PASEO 2.0 (AQ-8); project TIN2016-78011-C4-3-R (AEI/FEDER, UE).
Logos
