MetaEmbedding

Codes for our SIGIR-2019 paper:

Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings

This repo includes an example for training Meta-Embedding upon a deepFM model on the binarized MovieLens-1M dataset. The dataset is preprocessed and splitted already.

Requirements: Python 3 and TensorFlow.

Bibtex

@inproceedings{pan2019warm,
 author = {Pan, Feiyang and Li, Shuokai and Ao, Xiang and Tang, Pingzhong and He, Qing},
 title = {Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings},
 booktitle = {Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '19)},
 year = {2019},
 location = {Paris, France},
 doi = {10.1145/3331184.3331268}
}