Combine with Dependency Parsing and Entity for Answer Syntax Pattern Learning Method

被引：0

作者：

Zhao Xing ^{[1
]}

Yu Zheng-Tao ^{[1
]}

Zou Jun-Jie ^{[1
]}

Guo Jian-Yi ^{[1
]}

Mao Cun-Li ^{[1
]}

机构：

[1] Kunming Univ Sci & Technol, Sch Informat & Automat, Kunming 650051, Peoples R China

来源：

2011 30TH CHINESE CONTROL CONFERENCE (CCC) | 2011年

关键词：

Tourism Domain; Answer Extraction; Dependency Syntax Pattern; Domain Entity;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

For characteristics of the sentence patterns in restricted domain question-answer system, we proposed an answer syntax pattern learning method combined with dependency syntax and sentence patterns of domain answers entity. Firstly, this method uses labeled type of questions and answers to recall candidate snippets, then dependency parsing and entity recognition are conducted on the snippets to extract the candidate answer sentence patterns. Next, extend the same type of entities to obtain new candidate answer sentence patterns. Finally, get the candidate answer syntax pattern corpus according to the weight of candidate pattern calculated by the frequency and precision of the answers, which retrieved by the candidate patterns. We experimented on the answers extracting by pattern matching, the experimental on web data sets and the accessed pattern data sets show that the pattern learning method could effectively improve the results of extracting answers in the restricted domain.

引用

页码：3282 / 3286

页数：5