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A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation (2019)
Journal Article
Polatidis, N., Pimenidis, E., Fish, A., & Kapetanakis, S. (2019). A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation. International Journal on Artificial Intelligence Tools, 28(8), Article 1960011. https://doi.org/10.1142/S021821301960011X

Recommender systems' evaluation is usually based on predictive accuracy and information retrieval metrics, with better scores meaning recommendations are of higher quality. However, new algorithms are constantly developed and the comparison of result... Read More about A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation.

A switching multi-level method for the long tail recommendation problem (2019)
Journal Article
Alshammari, G., Jorro-Aragoneses, J. L., Polatidis, N., Kapetanakis, S., Pimenidis, E., & Petridis, M. (2019). A switching multi-level method for the long tail recommendation problem. Journal of Intelligent and Fuzzy Systems, 37(6), 7189-7198. https://doi.org/10.3233/JIFS-179331

© 2019 - IOS Press and the authors. All rights reserved. Recommender systems are decision support systems that play an important part in generating a list of product or service recommendations for users based on the past experiences and interactions.... Read More about A switching multi-level method for the long tail recommendation problem.

An explanation-based approach for experiment reproducibility in recommender systems (2019)
Journal Article
Polatidis, N., Papaleonidas, A., Pimenidis, E., & Iliadis, L. (in press). An explanation-based approach for experiment reproducibility in recommender systems. Neural Computing and Applications, https://doi.org/10.1007/s00521-019-04274-x

© 2019, Springer-Verlag London Ltd., part of Springer Nature. The offline evaluation of recommender systems is typically based on accuracy metrics such as the Mean Absolute Error and the Root Mean Squared Error for error rating prediction and Precisi... Read More about An explanation-based approach for experiment reproducibility in recommender systems.