A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation

Research output: Contribution to journalArticleResearchpeer-review

Original languageEnglish
JournalInternational Journal on Artificial Intelligence Tools
Publication statusAccepted/In press - 22 Jul 2019

Keywords

  • Recommender systems
  • Evaluation
  • Reproducibility
  • Replication

Cite this

@article{110c351e04c14f77a102213a3f13e65e,
title = "A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation",
keywords = "Recommender systems, Evaluation, Reproducibility, Replication",
author = "Nikolaos Polatidis and Elias Pimenidis and Andrew Fish and Stelios Kapetanakis",
year = "2019",
month = "7",
day = "22",
language = "English",
journal = "International Journal on Artificial Intelligence Tools",
issn = "1793-6349",
publisher = "World Scientific Publishing Company",

}

TY - JOUR

T1 - A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation

AU - Polatidis, Nikolaos

AU - Pimenidis, Elias

AU - Fish, Andrew

AU - Kapetanakis, Stelios

PY - 2019/7/22

Y1 - 2019/7/22

KW - Recommender systems

KW - Evaluation

KW - Reproducibility

KW - Replication

M3 - Article

JO - International Journal on Artificial Intelligence Tools

JF - International Journal on Artificial Intelligence Tools

SN - 1793-6349

ER -