CAJ | 학술논문

该本的多词串抽取是自然语言处理领域一项重要的研究内容.该文提出了一种多类别C-value(Multi-Class C-value)方法,利用多词串在不同领域的分布信息改善领域相关的多词串抽取的性能.在汽车、科技和旅行三个领域的数据上进行实验,评价多词串的准确率,在top-100级别上,较传统的C-value方法在三个领域中分别提高了12、12和13个百分点.实验结果验证了方法的有效性.
해본적다사천추취시자연어언처리영역일항중요적연구내용.해문제출료일충다유별C-value(Multi-Class C-value)방법,이용다사천재불동영역적분포신식개선영역상관적다사천추취적성능.재기차、과기화여행삼개영역적수거상진행실험,평개다사천적준학솔,재top-100급별상,교전통적C-value방법재삼개영역중분별제고료12、12화13개백분점.실험결과험증료방법적유효성.
Automatic multi-word terms extraction attracts more and more attention in the research of natural language processing. This paper proposes a Multi-Class C-value method, which uses the distribution of multi-word terms in different domains, to improve the performance of multi-word terms extraction. In the experiment with the data of automobile, technology and trip, the precisions of top 100 multi-word terms are 12%, 12% and 13% higher than the clssical C-value method in three domains respectively.