Acquisition and Optimization of Rules for Part of Speech Tagging
Jingbo Zhu · Terminology Standardization & Information Technology · 2004
A learning algorithm is presented to acquire and optimize rules which are applied on part of speech tagging. It can increase the tagging precision and efficiency. Applying the algorithm, an experiment is conducted with PTR corpus. Comparing with tagged result of grammatical tagging based on NA assumption, the tagging precision increases 5.53% in close text and 4.57% in open text.