Please use this identifier to cite or link to this item:
https://ruomo.lib.uom.gr/handle/7000/290
Title: | A multi-level collaborative filtering method that improves recommendations |
Authors: | Polatidis, Nikolaos Georgiadis, Christos K. |
Type: | Article |
Subjects: | FRASCATI::Natural sciences::Computer and information sciences |
Keywords: | cs.IR |
Issue Date: | 15-Apr-2016 |
Publisher: | Elsevier |
Source: | Polatidis, Nikolaos, and Christos K. Georgiadis. A multi-level collaborative filtering method that improves recommendations. Expert Systems with Applications 48 (2016): 100-110 |
Volume: | 48 |
First Page: | 100 |
Last Page: | 110 |
Abstract: | Collaborative filtering is one of the most used approaches for providing recommendations in various online environments. Even though collaborative recommendation methods have been widely utilized due to their simplicity and ease of use, accuracy is still an issue. In this paper we propose a multi-level recommendation method with its main purpose being to assist users in decision making by providing recommendations of better quality. The proposed method can be applied in different online domains that use collaborative recommender systems, thus improving the overall user experience. The efficiency of the proposed method is shown by providing an extensive experimental evaluation using five real datasets and with comparisons to alternatives. |
URI: | https://doi.org/10.1016/j.eswa.2015.11.023 https://ruomo.lib.uom.gr/handle/7000/290 |
ISSN: | 09574174 |
Other Identifiers: | 10.1016/j.eswa.2015.11.023 |
Appears in Collections: | Department of Applied Informatics |
Files in This Item:
File | Description | Size | Format | |
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Georgiadis_2016_A Multi Level.pdf | 232,96 kB | Adobe PDF | View/Open |
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