A large number of conflict events are affecting the world all the time. In order to analyse such conflict events effectively, this paper presents a Classification-Aware Neural Topic Model (CANTM-IA) for Conflict Information Classification and Topic Discovery. The model provides a reliable interpretation of classification results and discovered topics by introducing interpretability analysis. At the same time, interpretation is introduced into the model architecture to improve the classification performance of the model and to allow interpretation to focus further on the details of the data. Finally, the model architecture is optimised to reduce the complexity of the model.

翻译：大量冲突事件时刻影响着世界。为有效分析此类冲突事件，本文提出了一种用于冲突信息分类与主题发现的分类感知神经主题模型（CANTM-IA）。该模型通过引入可解释性分析，为分类结果和发现的主题提供了可靠的解释。同时，将解释机制融入模型架构中，以提升模型的分类性能，并促使解释进一步聚焦数据细节。最后，对模型架构进行了优化，以降低模型复杂度。