微博语料分词及标注方法初探  

Preliminary Study of Chinese Word Segmentation and Part-of-Speech Tagging Being Used for Microblog Data

作　　者：于清[1] 阿里甫.库尔班 

机构地区：[1]新疆大学信息科学与工程学院,新疆乌鲁木齐830046

出　　处：《新疆大学学报（自然科学版）》2013年第1期81-86,共6页Journal of Xinjiang University(Natural Science Edition)

基　　金：国家自然科学基金(61163029)

摘　　要：本文将清华大学中文分词和词性标注系统应用于部分微博语料数据,检测系统对微博新词识别能力及对识别错误进行了分类总结,并对识别率低的新词制定了标注规范.通过人工校对获得新的训练语料数据集,提高系统对微博文本的处理能力,为建立微博专用语料库做前期准备工作.In this paper, Tsinghua University’s Chinese word segmentation and part-of-speech tagging system is used to analyze microblog data .One finding is that the system cannot identify most of new words in microblog data, Identification errors are systematically classified and analyzed. An annotation guideline is designed to identify new words manually. The goal is to build manually annotated training data, improve the performance of microblog new word identification, and prepare for building microblog corpus for a specific purpose.

关 键 词：分词 标注系统 专有名词 新词 微博语料库 

分 类 号：TP391.2[自动化与计算机技术—计算机应用技术]