Invoice trade name classification method, system and equipment and computer readable storage medium

Abstract

The application discloses an invoice trade name classification method, system and equipment and a computer readable storage medium. The method comprises the following steps: determining the trade namevector of a to-be-classified invoice trade name based on preset rules; inputting the trade name vector to a pre-created target trained model to obtain an invoice trade name type output by the targettrained model, for judging if the type is a target type, wherein the target trained model is obtained by pre-utilizing target training samples to train a to-be-trained model created by the Extreme Gradient Boosting (XGBoost) model based on the gradient boosting decision tree, and the target training samples include training samples marked with target invoice trade name types and training samples obtained based on Rocchio algorithm and not marked with the trade name types. By using the invoice trade name classification method provided by the invention, the labour cost can be reduced and the accuracy of classification results can be obviously improved.

Description

technical field [0001] The invention relates to the technical field of automatic classification, in particular to a method, system, equipment and computer-readable storage medium for classifying commodity names of invoices. Background technique [0002] There are many types of invoices, each of which has a specific scope of use. It is very common to classify invoices in real life, and among the many information of invoices, such as product name, invoice unit price, ticket purchasing company, billing company, etc., it is a relatively common method to use product names to classify invoices. practice. According to the product name on the invoice, "Daohuaxiang rice" is classified into the grain category, and "Xiaomi mobile phone" is classified under electronic products. [0003] In existing solutions, categories are generally judged based on keyword matching. For example, for wine, some words such as "wine", "Maotai", and "alcohol" are prepared in advance. Words that coincide...

AI Technical Summary

Problems solved by technology

However, the product names are numerous and complex, and the process of preparing keywords requires a lot of manpower. For each special category, it is necessary to prepare a dedicated keyword library in advance.

In addition, if you only match characters, you will miss the semantic relationship, so the result of relying on keyword matching is not necessarily accurate

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