计算机技术与发展2012，Vol.22Issue(1)：119-121,125,4.
网络舆情监控中新词识别问题的研究
Research of New Word Pattern Recognization in Network Monitoring Public Opinion
摘要
Abstract
With rapid development and deepen evolution of internet public opinion in the internet,a variety of new vocabulary and new string comes out due to the sudden of matters and the high frequence of Mew words occur on network, therefore, the current method of sub -dictionary has no effect on them in a large extent. The most important and most deadly is that those rare appear strings are divided into scattered fragments by the existing segmentation system, which will greatly affect the accuracy in extracting out the hot words and the keywords. Know that the situation will become the bottleneck of improving performance in network monitoring system. It analyzes the major advantages and disadvantages of several word segmentation and draw out the characteristics,using the local high-frequency of the keyword not included into dictionary in the monitoring public opinion,then calculating the anomalous bond between the abnormal words and its around words,finally,to identify the keywords not edit. The experiment shows:compared to the traditional segmentation algorithm, this segmentation algorithm can identify the keywords better and is more suitable for network monitoring public opinion.关键词
网络舆情监控/新词识别/分词词典Key words
network monitoring public opinion/new word pattern recognization/dictionary分类
信息技术与安全科学引用本文复制引用
唐籍涛,李飞,郭昌松..网络舆情监控中新词识别问题的研究[J].计算机技术与发展,2012,22(1):119-121,125,4.基金项目
四川省教育科研项目(川教函[2011]210号) （川教函[2011]210号）
