Event recognition model optimization method, device and equipment and readable storage medium

Abstract

The invention discloses an event recognition model optimization method, device and equipment and a readable storage medium, and the method comprises the steps: inputting training texts corresponding to various types of events into a character event information extraction module, and extracting and obtaining the associated information of each character in the training texts and the character eventsof the various types of events; inputting the character event associated information and the training text into an event classification module for classification to obtain an event classification result corresponding to the training text; inputting the character event associated information and the keyword label corresponding to the training text into a keyword identification module for identification to obtain keyword identification loss; and calculating classification loss based on the event classification result and the event type label corresponding to the training text, and optimizing keyword identification loss and classification loss to optimize an event identification model. According to the method, the event keyword information is added as event classification guidance, so that the problem of event recognition errors caused by insufficient understanding or directivity errors of the model to the events is avoided, and the event classification accuracy is improved.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to an event recognition model optimization method, device, equipment and readable storage medium. Background technique [0002] In many current financial scenarios, it is necessary to analyze many financial events reported by the media to help investment decisions, and even build quantitative financial modeling indicators. Event recognition (Event Detective, ED) is to identify the type of events in the text. A current event recognition method is an event multi-classification method without trigger words. A large number of texts of various event types are used to train the multi-classification model in advance, and the trained event multi-classification model is used for event recognition. Due to the large number of event categories and fine division, and the small sample size of some categories of events, the accuracy of event recognition by the event multi-...

AI Technical Summary

Problems solved by technology

[0003] The main purpose of the present invention is to provide an event recognition model optimization method, device, equipment and readable storage medium, aiming at the problem that the accuracy rate of event recognition in the current event multi-classification model is not high

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