Embeddings Learning Task

An Embeddings Learning Task is a representation learning task that learns dense vectors.

• See: Distributional Vector Representation Learning.

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References

2018

• (Wang et al., 2019) ⇒ Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng, and Tat-Seng Chua. (2019). “Neural Graph Collaborative Filtering.” In: Proceedings of the 42nd international ACM SIGIR conference on Research and development in Information Retrieval.
  • QUOTE: Learning vector representations (aka. embeddings) of users and items lies at the core of modern recommender systems. Ranging from early matrix factorization to recently emerged deep learning based methods, existing efforts typically obtain a user's (or an item's) embedding by mapping from pre-existing features that describe the user (or the item), such as ID and attributes. …

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