Short text entity correlation identification method and system, electronic equipment and storage medium

Abstract

The invention discloses a short text entity correlation identification method and system, electronic equipment and a storage medium. The method comprises the following steps: fusing a word vector containing entity context semantic information, a position vector containing entity position coding information and a pre-coding vector containing entity pre-coding information to obtain a fused word vector of words in a training text; inputting the fusion word vector of the words of each training text into a TDLSTM model to obtain a forward vector code and a backward vector code, splicing the forward vector code and the backward vector code to obtain an entity splicing vector, and processing the entity splicing vector through a feedforward neural network to obtain a classification coding vector of each training text, normalizing the classification coding vector, obtaining a loss function according to the normalized classification coding vector, and carrying out iterative optimization on the loss function to obtain an optimal model; inputting a to-be-recognized short text into the optimal model to obtain a recognition result of the to-be-recognized text; the accuracy of short text entity correlation recognition is realized.

Description

technical field [0001] The invention relates to the field of text processing, in particular to a short text entity correlation identification method, system, electronic equipment and storage medium. Background technique [0002] At present, the processing methods of text entity correlation are mainly divided into two categories: machine learning-based and neural network-based. [0003] The method based on machine learning is mainly to manually construct the feature information of the text, and then use the machine learning classifier to classify the feature information. Commonly used feature classifiers include Support Vector Machine (Support Vector Machine, SVM) and Naive Bayesian. In traditional machine learning methods, the construction of features is very important, which is the key to determining the accuracy rate. A lot of feature engineering work is required, and the extraction and construction of feature information is not comprehensive, which leads to the failure of...

AI Technical Summary

Problems solved by technology

[0005] In view of this, the embodiment of the present invention provides a short text entity correlation identification method, system, electronic device and storage medium to solve the problem of inaccurate short text entity correlation identification in the prior art

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