Social Recommender Systems

Guy, Ido

doi:10.1007/978-1-0716-2197-4_22

Cited by 5 publications

(2 citation statements)

References 63 publications

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“…Additional information, such as product tags or categories, can be directly utilized to ascertain a user's preferences. For example, the categories of films or music albums can indicate the types of films and music they prefer (Guy, 2022). Leveraging this accessible social data in recommender systems can enhance prediction accuracy.…”

Section: Social Tagging Recommender Systemsmentioning

confidence: 99%

Social Recommender System Based on CNN Incorporating Tagging and Contextual Features

Alrashidi,

Selamat,

Ibrahim

et al. 2024

Journal of Cases on Information Technology

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The Internet's rapid growth has led to information overload, necessitating recommender systems for personalized suggestions. While content-based and collaborative filtering have been successful, data sparsity remains a challenge. To address this, this article presents a novel social recommender system based on convolutional neural networks (SRSCNN). This approach integrates deep learning and contextual information to overcome data sparsity. The SRSCNN model incorporates user and item factors obtained from a neural network architecture, utilizing features from item titles and tags through a CNN. The authors conducted extensive experiments with the MovieLens 10M dataset, demonstrating that the SRSCNN approach outperforms state-of-the-art baselines. This improvement is evident in both rating prediction and ranking accuracy across recommendation lists of varying lengths.

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Section: Social Tagging Recommender Systemsmentioning

confidence: 99%

Social Recommender System Based on CNN Incorporating Tagging and Contextual Features

Alrashidi,

Selamat,

Ibrahim

et al. 2024

Journal of Cases on Information Technology

View full text Add to dashboard Cite

show abstract

“…Nowadays, the Internet is highly needed in people's lives, as people are dependent for performing routine activities such as making necessary purchases, conducting financial transactions, and entertainments, among others. Businesses like to use this opportunity to provide services and products to customers [1][2][3], as companies such as Amazon, Yahoo, Netflix, Facebook, and IMDB benefit from this technology [4,5]. Providing online shopping is not enough anymore to survive in the competitive market for the e-commerce world, as customers may easily visit different stores and vendors.…”

Section: Introductionmentioning

confidence: 99%