May 19, 2021 · In this paper, we propose Graph Meta Embedding (GME) models that can rapidly learn how to generate desirable initial embeddings for new ad IDs based on graph ...

Jul 11, 2021 · Experimental results on three real-world datasets show that GMEs can significantly improve the prediction performance in both cold-start (i.e., ...

We need to prepare two datasets: one for the main CTR prediction model (including pre-training and warm-up training) and the other for the GME model (i.e., ...

May 19, 2021 · Experimental results on three real-world datasets show that GMEs can significantly improve the prediction performance in both cold-start and ...

Well-learned ID embeddings can greatly improve the prediction accuracy of cold-start items compared to methods that do not use ID inputs [16][17] [18] . In this ...

Learning Graph Meta Embeddings for Cold-Start Ads in Click-Through Rate Prediction.pdf · Latest commit · History · Breadcrumbs.

Learning Graph Meta Embeddings for Cold-Start Ads in Click-Through Rate Prediction ... For existing old ads, GMEs first build a graph to connect them with new ads ...

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This approach has shown notable success in enhancing the accuracy of click-through rate predictions. However, prevalent meta-embedding models often focus solely ...

Experimental results showed that Meta-Embedding can significantly improve both the cold-start and warm-up performances for six existing CTR prediction ...