本文介绍了推荐系统领域的多种核心模型，包括Factorization Machines、Bayesian Factorization Machines、DeepFM、Neural Factorization Machines等，这些模型广泛应用于CTR预测、稀疏预测分析、特征交互权重学习及上下文感知推荐等场景。
推荐系统常用模型
- Factorization Machines
- Bayesian Factorization Machines
- DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
- Neural Factorization Machines for Sparse Predictive Analytics
- Attentional Factorization Machines:Learning the Weight of Feature Interactions via Attention Networks
- Neural Attentive Item Similarity Model for Recommendation
- Convolutional Factorization Machines for Context-Aware Recommendation
- InteractionNN: A Neural Network for Learning Hidden Features in Sparse Prediction
Factorization Machines
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Bayesian Factorization Machines
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DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
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Neural Factorization Machines for Sparse Predictive Analytics
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Attentional Factorization Machines:Learning the Weight of Feature Interactions via Attention Networks
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Neural Attentive Item Similarity Model for Recommendation
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Convolutional Factorization Machines for Context-Aware Recommendation
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InteractionNN: A Neural Network for Learning Hidden Features in Sparse Prediction
(等待更新…)
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