Self-learning event extraction method and application thereof

Abstract

The invention discloses a self-learning event extraction method and application thereof. The event extraction method comprises the steps that candidate words are subjected to self-learning screening through sentence vectors of event information and candidate word role mapping contained in each sentence vector, and a trigger word set is obtained; according to the invention, industrial production abnormal logs and other information can be quickly and accurately interpreted, and an appropriate decision is further made.

Description

technical field [0001] The present invention relates to the technical field of event extraction. Background technique [0002] Production anomalies refer to schedule delays or production shutdowns that occur during the production process, and generally include planning anomalies, material anomalies, equipment anomalies, process quality anomalies, design process anomalies, water and electricity anomalies, and other forms. Abnormal production will cause production waste and seriously affect the production capacity of the enterprise, which is an urgent problem to be overcome in production. In the solution to this problem, a common method is that decision makers interpret the abnormal logs of the industrial production process to find out information related to the abnormality, such as the cause, development process, etc., and make effective decisions based on this information. Reduce production exceptions. [0003] In the prior art, the interpretation of event information such...

AI Technical Summary

Problems solved by technology

In order to obtain accurate trigger word recognition, a large number of trigger word tags are required. In the existing technology, most of them are realized through manual tagging, which is not only cumbersome, error-prone, but also poor in coverage and portability.

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