一种融入背景知识的交互文本立场分析方法

This paper proposes a stance classification method on interactive text by incorporating background knowledge. This method retrieves relevant background knowledge texts from Wikipedia by using the interactive text as query. The retrieved background knowledge texts are encoded and then ultilized to learn the representation of relavent background knowledge through deep memory network for improving the representation learning of interactive text. The experimental results on three English online debate datasets show that the performance of interactive stance classification can be effectively improved by incorporating background knowledge through choosing the appropriate number of background knowledge embedding layers and the connection method of background knowledge embedding layer.