Fast and Discriminative Semantic Embedding
We present a novel, effective and efficient method for term and document embedding method. Our experiments show it outperforms state-of-the-art methods in terms of the STS benchmark and subject prediction when trained on the same datasets, while at the same time being computationally cheaper by orders of magnitude.
27 May 2019
13th International Conference on Computational Semantics
- Semantic Embedding