An SVMTool-Based Chinese POS Tagger
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TL;DR
SVMTool is applied in Chinese POS tagging task and improves the accuracy by 2.07% compared with the baseline system on the Hidden Markov Model, and some features of Chinese characters and words are introduced to improve the accuracy of unknown words.
Abstract
The SVMTool is a simple,flexible and effective generator of sequential tagger based on Support Vector Machines,capable of dealing with a large number of linguistic features.In this paper.SVMTool is applied in Chinese POS tagging task and improves the accuracy by 2.07%compared with the baseline system on the Hidden Markov Model.To further improve the accuracy of unknown words,we introduce some features of Chinese characters and words,such as radicals of Chinese characters and reduplicate words,and probe into a theoretical analysis for their feasibility.Experiments indicate that these features can improve the accuracy of unknown words by 1.16% as well as reduce the error rate by 7.40%.