摘要
提出一种改进C-value的术语抽取方法,即IC-value方法。利用停用词对文本进行预处理后,采用一种基于串频统计的抽取算法提取候选术语;对候选术语进行语言规则过滤;从逆文档频率、破碎子串和术语长度三个方面改进C-value方法得到IC-value方法,并用来计算候选术语的术语度。以1 000篇乙型肝炎相关论文摘要进行实证研究,结果证明IC-value方法在准确率和召回率方面都要优于C-value、TF-IDF和V-value,有较强的长术语发现能力,且识别破碎子串的效果十分明显。
An improved C -value term extraction method is introduced in the paper. Firstly, the domain -specific text corpora is preprocessed by stop word list. Secondly, a term extraction algorithm based on the co - occurrence frequency of multi -character is applied to get candidate terms. Lastly, term selection is completed based on termbood computed by IC - value which is the improvement of C - value in terms of inverse document frequency, meaningless substring and term length. Empirical study is conducted based on 1 000 abstracts of articles about Hepatitis B. The results indicate the pro- posed IC - value is much better than C - value, TF - IDF and V - value in both precision and recall. And IC - value also has good performance in long term extraction and it is very effective in filtering meaningless substring.
出处
《现代图书情报技术》
CSSCI
北大核心
2013年第2期24-29,共6页
New Technology of Library and Information Service
关键词
术语抽取
串频统计
语言规则
术语度
Term extraction Statistics of string frequency Linguistical rules Termhood
