A New Algorithm of Rule Generation for Chinese Information Extraction

摘要

Learning rules automatically is a hot and difficult topic in information extraction. This paper proposes an algorithm for rule generation in Chinese information extraction - RGA-CIE, which is domain independent for free, text of Chinese. RGA-CIE applies supervised learning with bottom-up strategy, which is a rule generalization process with a heuris'tic method to decide rule generalization path and Laplacian formula to evaluate the performance of rules. The learned rules have been applied to the experimental system-CIIES (Comprehensive Information Based Chinese Information Extraction System), and achieved good result, which proves the feasibility and effectiveness of RGA-CIE.