黄德根Huang Degen

(教授)

 博士生导师  硕士生导师
学位:博士
性别:男
毕业院校:大连理工大学
所在单位:计算机科学与技术学院
电子邮箱:huangdg@dlut.edu.cn

论文成果

Translation oriented sentence level collocation identification and extraction

发表时间:2019-03-11 点击次数:

论文名称:Translation oriented sentence level collocation identification and extraction
论文类型:会议论文
收录刊物:EI
卷号:787
页面范围:78-89
摘要:The technique to identify and extract collocations in a given sentence is very important to sentence understanding, analysing and translating. So we propose a sentence level collocation identification and extraction method which follows the traditional two phase collocation extraction model. In candidate generating phase, we use the dependency parsing results directly, while in the filtering phase, we propose to use the latest model of distributional semantics - word embedding based similarity to filter the noises. For each candidate, three word embedding based similarity rankings will be obtained and accordingly to decide if it is a real collocation. The experimental results show that the proposed filtering method performs better than the traditional well-known association measures. The comparison with the baseline system shows that the proposed method can retrieve more collocations with higher precision than the baseline, which is of significance to sentence related natural language processing tasks. © Springer Nature Singapore Pte Ltd. 2017.
发表时间:2017-09-27