Nikolaos Polatidis
Fast and accurate evaluation of collaborative filtering recommendation algorithms
Polatidis, Nikolaos; Kapetanakis, Stelios; Pimenidis, Elias; Manolopoulos, Yannis
Authors
Stelios Kapetanakis
Dr Elias Pimenidis Elias.Pimenidis@uwe.ac.uk
Senior Lecturer in Computer Science
Yannis Manolopoulos
Contributors
Ngoc Thanh Nguyen
Editor
Tien Khoa Tran
Editor
Ualsher Tukayev
Editor
Tzung-Pei Hong
Editor
Bogdan Trawiński
Editor
Edward Szczerbicki
Editor
Abstract
Collaborative filtering are recommender systems algorithms that provide personalized recommendations to users in various online environments such as movies, music, books, jokes and others. There are many such recommendation algorithms and, regarding experimental evaluations to find which algorithm performs better a lengthy process needs to take place and the time required depends on the size of the dataset and the evaluation metrics used. In this paper we present a novel method that is based on a series of steps that include random subset selections, ensemble learning and the use of well-known evaluation metrics Mean Absolute Error and Precision to identify, in a fast and accurate way, which algorithm performs the best for a given dataset. The proposed method has been experimentally evaluated using two publicly available datasets with the experimental results showing that the time required for the evaluation is significantly reduced, while the results are accurate when compared to a full evaluation cycle.
Citation
Polatidis, N., Kapetanakis, S., Pimenidis, E., & Manolopoulos, Y. (2022). Fast and accurate evaluation of collaborative filtering recommendation algorithms. In N. Thanh Nguyen, T. Khoa Tran, U. Tukayev, T. Hong, B. Trawiński, & E. Szczerbicki (Eds.), ACIIDS 2022: Intelligent Information and Database Systems (623-634). https://doi.org/10.1007/978-3-031-21743-2_50
Conference Name | 14th Asian Conference on Intelligent Information and Database Systems |
---|---|
Conference Location | Ho Chi Minh City, Vietnam |
Start Date | Nov 28, 2022 |
End Date | Nov 30, 2022 |
Acceptance Date | Mar 16, 2021 |
Online Publication Date | Dec 9, 2022 |
Publication Date | Dec 9, 2022 |
Deposit Date | Apr 27, 2022 |
Publicly Available Date | Mar 29, 2024 |
Electronic ISSN | 1611-3349 |
Publisher | Springer Verlag |
Volume | 13757 LNAI |
Pages | 623-634 |
Series Title | Lecture Notes in Computer Science (LNCS, volume 13757) |
Series ISSN | 1611-3349; 0302-9743 |
Book Title | ACIIDS 2022: Intelligent Information and Database Systems |
Chapter Number | 50 |
ISBN | 9783031217425 |
DOI | https://doi.org/10.1007/978-3-031-21743-2_50 |
Keywords | Recommender Systems; Collaborative Filtering; Evaluation; Mean Absolute Error; Precision |
Public URL | https://uwe-repository.worktribe.com/output/9422042 |
Publisher URL | https://link.springer.com/chapter/10.1007/978-3-031-21743-2_50 |
Related Public URLs | https://link.springer.com/book/9783031219689 https://www.springer.com/series/558 https://link.springer.com/conference/aciids |
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Fast and accurate evaluation of collaborative filtering recommendation algorithms
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Copyright Statement
This is the accepted manuscript. The final published version is available at: https://doi.org/10.1007/978-3-031-21743-2_50
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