面向中文微博的评价对象与评价词语联合抽取

doi:10.3969/j.issn.0372-2112.2016.07.021

电子学报 ›› 2016, Vol. 44 ›› Issue (7): 1662-1670.DOI: 10.3969/j.issn.0372-2112.2016.07.021

面向中文微博的评价对象与评价词语联合抽取

刘全超, 黄河燕, 冯冲

北京理工大学计算机学院, 北京 100081

收稿日期:2015-01-29 修回日期:2015-07-02 出版日期:2016-07-25 发布日期:2016-07-25
作者简介:刘全超 男,1982年生于河北,博士研究生,主要研究方向为情感计算、信息抽取;黄河燕 女,1963年生于湖南,教授,博士生导师,主要研究领域为自然语言处理、机器翻译
基金资助:
国家973重点基础研究发展计划(No.2013CB329605)

Co-Extracting Opinion Targets and Opinion-Bearing Words in Chinese Micro-Blog Texts

LIU Quan-chao, HUANG He-yan, FENG Chong

Department of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China

Received:2015-01-29 Revised:2015-07-02 Online:2016-07-25 Published:2016-07-25

摘要/Abstract

摘要：

深入挖掘微博内容中评价对象与评价词语的词法特征、句法特征、语义特征以及相对位置特征,提出评价对象与评价词语的序列化联合抽取模型.进一步结合微博间转发关系特性提出基于转发关系的联合抽取优化算法.并与相关算法进行实验对比,对实验结果进行了综合分析,证明了方法的可行性和优越性.

关键词: 观点挖掘, 信息抽取, 社交网络, 评价对象, 评价词语, 微博

Abstract:

Using lexical,syntactic,semantic and relative position features to extract opinion pairs in micro-blog,we put forward the co-extracting model,and then give co-extracting opinion pairs optimization algorithm based on forwarding between micro-blogs.According to the experimental results,our two-stage approach greatly improves the performances of co-extracting opinion pairs.

Key words: opinion mining, information extraction, social network, opinion target, opinion-bearing word, micro-blog

中图分类号:

TP391

刘全超, 黄河燕, 冯冲. 面向中文微博的评价对象与评价词语联合抽取[J]. 电子学报, 2016, 44(7): 1662-1670.

LIU Quan-chao, HUANG He-yan, FENG Chong. Co-Extracting Opinion Targets and Opinion-Bearing Words in Chinese Micro-Blog Texts[J]. Acta Electronica Sinica, 2016, 44(7): 1662-1670.

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面向中文微博的评价对象与评价词语联合抽取

Co-Extracting Opinion Targets and Opinion-Bearing Words in Chinese Micro-Blog Texts

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