基于结构化事件的主题表示.

Topic models based on bag-of-words got topics represented by individual words which were difficult to understand. This paper thus proposed using events as documents’ terms, meanwhile, considered Biterm topic model combined with GPU model which incorporated event correlation knowledge for inference, alleviated the adverse effect of event sparsity from co-occurrence and semantic two aspects. Experimental results show that the proposed method guarantees both interpretable and coherent topics. [ABSTRACT FROM AUTHOR]