paper

Multi-Context Term Embeddings: the Use Case of Corpus-based Term Set Expansion

arXiv:1904.02496

Abstract

In this paper, we present a novel algorithm that combines multi-context term embeddings using a neural classifier and we test this approach on the use case of corpus-based term set expansion. In addition, we present a novel and unique dataset for intrinsic evaluation of corpus-based term set expansion algorithms. We show that, over this dataset, our algorithm provides up to 5 mean average precision points over the best baseline.

6 pages, RepEval 2019 (NAACL-HLT workshop)

Multi-Context Term Embeddings: the Use Case of Corpus-based Term Set Expansion · wovepaper