基于条件随机场的评价对象抽取

评价对象抽取是情感分析的重要组成部分，针对在线商品中文评论非正规化、网络化的特点，本文提出一种基于句法分析和条件随机场的评价对象的抽取方法，通过实验分析不同模板与不同特征组合对评价对象提取的F值的影响.在系统实现上，主要利用哈工大语言技术平台（LTP）的开放接口和CRFs开源工具对评论数据集进行训练和测试.最终使两类数据集的评价对象抽取的F值达分别达到到82.98%和83.50%.

Objects Extraction of Comment Based on Conditional Random Field

Extracting object of comment is an important part of emotional analysis. In view of the irregularity of language and the characteristics of network in Chinese online comment, this paper presents a method of extracting objects based on the syntactic analysis and conditional random field. It analyzes experimentally the effect of different templates and different combinations of features on the F value. In the implementation of the system, this paper uses Harbin Institute of Technology language platform open interface and CRFs open source tools to train and test on comment data sets. Finally, the F values of the two types of data sets have reached 82.98% and 83.50% respectively.