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Improving recommendations utilizing users’ demographic information
The exponential increase in digital data has increased the amount of available online information. This complicates the user’s decision-making. Most online merchants and service providers utilize recommendation systems to solve this problem and meet customer needs. The traditional collaborative filt...
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Published in: | Quality & quantity 2024-12, Vol.58 (6), p.5559-5575 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | The exponential increase in digital data has increased the amount of available online information. This complicates the user’s decision-making. Most online merchants and service providers utilize recommendation systems to solve this problem and meet customer needs. The traditional collaborative filtering based approach faces enormous challenges in providing potential personalized recommendation results. The demographic information of users may improve personalized recommendation results. This research proposes an improved recommendation approach based on users’ demographic information. Compared with traditional collaborative filtering-based approaches, this approach provides improved results. The experimental results show the enhanced prediction accuracy of the proposed approach and significantly lower errors when experimenting with the MovieLens dataset. |
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ISSN: | 0033-5177 1573-7845 |
DOI: | 10.1007/s11135-024-01890-1 |