Enhancing Movie Recommendation Systems with Hybrid Collaborative Filtering, Content-based Filtering and SVD

The swift advancement of Internet technology has intensified the issue of information overload. Consequently, users face difficulties in efficiently navigating extensive data and locating content tailored to their interests. To handle this issue, this paper proposes an enhanced movie recommendation

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.4108/eai.21-11-2024.2354625
Primary Topic
Recommender Systems and Techniques
Type
article
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article

Enhancing Movie Recommendation Systems with Hybrid Collaborative Filtering, Content-based Filtering and SVD

Yu‐Wei Wu, Z. L. Guan, Liheng Xu
Recommender Systems and Techniques
article

Enhancing Movie Recommendation Systems with Hybrid Collaborative Filtering, Content-based Filtering and SVD

Yu‐Wei Wu, Z. L. Guan, Liheng Xu
article en

Abstract

The swift advancement of Internet technology has intensified the issue of information overload. Consequently, users face difficulties in efficiently navigating extensive data and locating content tailored to their interests. To handle this issue, this paper proposes an enhanced movie recommendation

Openalex Percentile: Top 94%
Recommender Systems and Techniques
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Enhancing Movie Recommendation Systems with Hybrid Collaborative Filtering, Content-based Filtering and SVD — Yu‐Wei Wu, Z. L. Guan, et al. · (2025) | TGRS Research Map | TGRS