Abstractive Summary of Public Opinion News Based on Element Graph Attention

Abstract

The summary of case–public opinion refers to the generation of case-related sentences from public opinion information related to judicial cases. Case–public opinion news refers to the judicial cases (intentional homicide, rape, etc.) that cause large public opinion. The public opinion news in these cases usually contains case element information such as the suspect, victim, time, place, process, and sentencing of the case. In the multi-document summary of case–public opinion, due to the problem of information cross and information redundancy between different documents under the same case, in order to generate a concise and smooth summary, this paper proposes an abstractive summary model of case–public opinion based on the attention of a case element diagram. Firstly, multiple public opinion documents in the same case are split into paragraphs, and then the paragraphs and case elements are coded based on the transformer method to construct a heterogeneous graph containing paragraph nodes and case element nodes. Finally, in the decoding process, the two-layer attention mechanism is applied to the case element node and paragraph node, so that the model can effectively solve the redundancy problem in summary generation.