Multilingual Event Detection Based on Cross-level and Multi-view Features Fusion
The goal of the multilingual event detection task is to organize a collection of news documents in multiple languages in-to different key events,where each event can include news documents in different languages.This task facilitates various down-stream task applications,such as multilingual knowledge graph construction,event reasoning,information retrieval,etc.At pre-sent,multilingual event detection is mainly divided into two methods:translation first and then event detection,and single lan-guage detection first and then alignment across multiple languages.The former relies on the effect of translation while the latter requires a separate training model for each language.To this end,this paper proposes a multilingual event detection method based on cross-level multi-view feature fusion,which performs end-to-end multilingual event detection tasks.This method uses the multi-view features of documents from different levels to obtain high reliability.It improves the generalization performance of low-resource language event detection.Experiments on a news dataset with a mixture of nine languages show that the proposed method improves the BCubed F1 value by 4.63％.
万方数据
维普
