Last update: June 2023
DataGenCARS: Generator of Synthetic Data for the Evaluation of Context-Aware Recommendation Systems
Brief description
DataGenCARS is a complete Java-based synthetic dataset generator for the evaluation of Context-Aware Recommendation Systems (CARS). The generator presents a high flexibility in the obtaining of datasets in several scenarios of items recommendation (with context or without context).
Some key features of Data-GenCARS are listed below:
- Flexible definition of user schemas, item schemas and context schemas.
- Flexible definition of user profiles.
- Realistic generation of ratings and attributes of items.
- The automatic mapping between item schemas and Java classes.
- The possibility to mix real and synthetic datasets and of replicating existing real datasets.
User's Manual
Software
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