首页 | 本学科首页   官方微博 | 高级检索  
     


Cross-Language Opinion Lexicon Extraction Using Mutual-Reinforcement Label Propagation
Authors:Zheng Lin  Songbo Tan  Yue Liu  Xueqi Cheng  Xueke Xu
Affiliation:Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.; National Institute of Genomic Medicine, Mexico,
Abstract:
There is a growing interest in automatically building opinion lexicon from sources such as product reviews. Most of these methods depend on abundant external resources such as WordNet, which limits the applicability of these methods. Unsupervised or semi-supervised learning provides an optional solution to multilingual opinion lexicon extraction. However, the datasets are imbalanced in different languages. For some languages, the high-quality corpora are scarce or hard to obtain, which limits the research progress. To solve the above problems, we explore a mutual-reinforcement label propagation framework. First, for each language, a label propagation algorithm is applied to a word relation graph, and then a bilingual dictionary is used as a bridge to transfer information between two languages. A key advantage of this model is its ability to make two languages learn from each other and boost each other. The experimental results show that the proposed approach outperforms baseline significantly.
Keywords:
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号