Characteristics of the Learning Data of a Session-Based Recommendation System and their Impact on the Performance of the System
Author:
Affiliation:
1. Białystok University of Technology, Poland
2. Lublin University of Technology, Poland
Publisher
University of Gdańsk
Reference17 articles.
1. 1. Adomavicius G., Zhang J.: Impact of data characteristics on recommender systems performance, ACM Transactions on Management Information Systems 3(1), 1-17 (2012)
2. Improving aggregate recommendation diversity using ranking-based techniques. IEEE Trans. Knowl;Adomavicius;Data Eng,2012
3. 3. Alharbey R. et al.: Modeling user rating pref. behavior to improve the performance of the collaborative filtering based recommender systems, PLOS ONE 14(8), (2019)
4. 4. Bellogin A., Deldjoo Y., Di Noia T.: Explaining recommender systems fairness and accuracy through the lens of data characteristics, Inform. Process.&Manag. 58 (5), (2021)
5. 5. Chin, J.Y. et al.: The Datasets Dilemma: How Much Do We Really Know About Recommendation Datasets? In: 15th ACM Int. Conf. WSDM '22, pp 141-149 (2022)
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