Semi-supervised URL Segmentation with Recurrent Neural Networks Pre-trained on Knowledge Graph Entities
Hao Zhang, Jae Hun Ro, Richard Sproat · 2020
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%.