Deep Neural Networks for YouTube Recommendations
Citations
2,647Â citations
Cites background from "Deep Neural Networks for YouTube Re..."
...We also do not consider non-deep learning approaches for generating item/content embeddings, since other works have already proven state-of-the-art performance of deep learning approaches for generating such embeddings [9, 12, 24]....
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1,695Â citations
1,317Â citations
Cites background or methods from "Deep Neural Networks for YouTube Re..."
...Most of the popular model structures [3, 4, 21] share a similar Embedding&MLP paradigm, which we refer to as base model, as shown in the left of Fig....
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...Deep Crossing [21], Wide&Deep Learning [4] and YouTube Recommendation CTR model [3] extend LS-PLM and FM by replacing the transformation function with complex MLP network, which enhances the model capability greatly....
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...As fully connected networks can only handle fixed-length inputs, it is a common practice [3, 4] to transform the list of embedding vectors via a pooling layer to get a fixed-length vector:...
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...Recently, inspired by the success of deep learning in computer vision [14] and natural language processing [1], deep learning based methods have been proposed for CTR prediction task [3, 4, 21, 26]....
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..., searched terms or watched videos in YouTube recommender system [3]....
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1,070Â citations
1,020Â citations
Cites background or methods from "Deep Neural Networks for YouTube Re..."
...Collaborative Filtering (CF) is a prevalent technique in modern recommender systems [7, 45]....
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...To alleviate information overload on the web, recommender system has been widely deployed to perform personalized information filtering [7, 45, 46]....
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References
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139,059Â citations
"Deep Neural Networks for YouTube Re..." refers background in this paper
...We observe that the most important signals are those that describe a user’s previous interaction with the item itself and other similar items, matching others’ experience in ranking ads [7]....
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30,843Â citations
24,012Â citations
"Deep Neural Networks for YouTube Re..." refers background in this paper
...A key advantage of using deep neural networks as a generalization of matrix factorization is that arbitrary continuous and categorical features can be easily added to the model....
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17,184Â citations
11,343Â citations