UPDF AI

Domain Adaptation via Pseudo In-Domain Data Selection

Amittai Axelrod,Xiaodong He,Jianfeng Gao

2011 · DBLP: conf/emnlp/AxelrodHG11
Conference on Empirical Methods in Natural Language Processing · 574 citations

TLDR

The results show that more training data is not always better, and that best results are attained via proper domain-relevant data selection, as well as combining in- and general-domain systems during decoding.