  Breaking domain names such as openresearch into component words open and
research is important for applications like Text-to-Speech synthesis and web
search. We link this problem to the classic problem of Chinese word
segmentation and show the effectiveness of a tagging model based on Recurrent
Neural Networks (RNNs) using characters as input. To compensate for the lack of
training data, we propose a pre-training method on concatenated entity names in
a large knowledge database. Pre-training improves the model by 33% and brings
the sequence accuracy to 85%.
