摘要
提出一种基于马尔科夫逻辑网的句子情感分析方法.与深度学习方法相结合实现跨领域的知识迁移,同时采用马尔科夫逻辑网将句子的上下文信息与其它情感特征相结合实现句子情感分析.在COAE评测数据上的实验结果表明,该方法与SVM分类方法相比,准确率达到70.02%,并且在跨领域的情感分析任务中也得到了较好的结果.
A new method for sentence sentimental analysis based on Markov logic network is proposed. With the combination of Markov logic network and deep learning methods, it could realize the cross domain knowledge migration. By the function of Markov logic network that could combine discourse information with other sentiment features of sentence, the proposed method could also realize the sentence sentiment orientated analysis. Experimental results on COAE data show that, compared with SVM method, this method could improve the precision considerably and achieve the high precision for implementing cross-domain sentimental analysis task.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2013年第6期600-604,共5页
Transactions of Beijing Institute of Technology
基金
北京市自然科学基金资助项目(4123094)
关键词
情感分析
马尔科夫逻辑网
深度学习
sentimental analysis Markov logic networks deep learning
