A reproducible POI recommendation framework: Works mapping and benchmark evaluation

This work is a companion reproducibility paper that presents a framework to reproduce our previous experiments and results reported in Werneck et al. (2021). In that previous paper, we introduced a systematic mapping process of points-of-interest (POI) recommendation methods and provided a uniform e...

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Detalles Bibliográficos
Autores: Werneck, Heitor, Silva, Nícollas, Pereira, Adriano, Carvalho, Matheus, Bellogin Kouki, Alejandro, Martínez Gil, Jorge, Mourão, Fernando, Rocha, Leonardo
Tipo de recurso: artículo
Fecha de publicación:2022
País:España
Institución:Universidad Autónoma de Madrid
Repositorio:Biblos-e Archivo. Repositorio Institucional de la UAM
Idioma:inglés
OAI Identifier:oai:repositorio.uam.es:10486/711201
Acceso en línea:http://hdl.handle.net/10486/711201
https://dx.doi.org/10.1016/j.is.2022.102019
Access Level:acceso abierto
Palabra clave:POI recommendation
Benchmark
Works mapping
Informática
Descripción
Sumario:This work is a companion reproducibility paper that presents a framework to reproduce our previous experiments and results reported in Werneck et al. (2021). In that previous paper, we introduced a systematic mapping process of points-of-interest (POI) recommendation methods and provided a uniform evaluation methodology based on metrics covering different aspects besides accuracy. Due to the lack of reproducible and extensible benchmarks, our work introduces a reproducibility framework for POI methods based on a collection of Python software libraries and a Docker image. Our proposal is composed of: (1) a package to perform a protocol that reproduces our systematic mapping process Werneck et al. (2021), containing all collected data, insightful views on current advances and opened challenges; and (2) an extensible benchmark to perform a protocol to reproduce experimental evaluations on POI recommendation, considering different datasets, metrics, and the strongest baselines in the literature. This work also demonstrates all processes required to instantiate its framework. Moreover, our work can be considered at least weakly reproducible, since we were able to reproduce the results of the previous paper, leading us to the same conclusions.