| |
| People read a comment on the web to learn about a product or some news, and the adjectives and nouns in these comments express important information. When we extract the adjective and nouns in the comments, If we can determine that there is indeed a relationship between the adjective and the noun, it will be very helpful for us to understand the comment. This thesis is all about extracting these word pairs and using transfer learning to extract them more quickly and accurately. This adjective and noun pair may undergo some changes in their relationship in different domains. This thesis considers the different domains to identify whether they are related or not. In this paper we propose an adversarial neural network approach with the help of a graphical model, DANN-G. This method considers the relationship between the bags well, the relationship within the bags, and thus reduces the noise caused by remote supervision in the common methods of relationship extraction. Our model has improved in the five major data sets of Amazon. |
|
| Keywords:relation extraction; transfer learning; graphical model; adversarial neural network; domain adaptation |
|
