MINING CHINESE COMPARATIVE SENTENCES BY SEMANTIC ROLE LABELING

摘要：

This paper studies the problem of mining Chinese comparative sentences in text documents by using Semantic Role Labeling (SRL). The comparative opinion can be divided into six semantic roles: Holder, Entity 1, Comparative predicates, Entity 2, Attributes and Sentiments. These six opinion elements were recognized and labeled by using SRL. A corpus of Chinese comparative sentences was manually labeled at first. Then a Conditional Random Fields (CRFs) model was trained by learn from the corpus. Finally new comparative sentences were labeled by using this CRFs model, and comparative relations were extracted afterward.

关键词： Opinion mining Comparative sentences Semantic role labeling Conditional random fields

作者: FENG HOU GUO-HUI LI

作者单位: School of information system and management, National University of Defense Technology, Changsha 410073, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 2563-2568

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）