Domain-Specific Chinese Word Segmentation with Document-Level Optimization

Previous studies normally formulate Chinese word segmentation as a character sequence labeling task and optimize the solution in sentence-level. In this paper, we address Chinese word segmentation as a document-level optimization problem. First, we apply a state-of-the-art approach, i.e., long short-term memory (LSTM), to perform character classification; Then, we propose a global objective function on the basis of character classification and achieve global optimization via Integer Linear Programming (ILP). Specifically, we propose several kinds of global constrains in ILP to capture various segmentation knowledge, such as segmentation consistency and domain-specific regulations, to achieve document-level optimization, besides label transition knowledge to achieve sentence-level optimization. Empirical studies demonstrate the effectiveness of the proposed approach to domain-specific Chinese word segmentation.