Data classification and model training method and device, storage medium and program product

By using a logistics big data language model to label and classify logistics service data, the problem of data classification difficulties in the logistics industry is solved, data management and utilization efficiency is improved, and the quality of logistics services is enhanced.

CN122087612APending Publication Date: 2026-05-26SF TECH CO LTD
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Patent Information

Application Number
CN202411718376.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-11-26
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

In the logistics industry, the data generated by couriers and customers during the delivery process is difficult to classify and organize quickly and effectively. Existing technologies based on rules or simple machine learning have limited performance, resulting in low efficiency in data management and utilization.

Method used

A logistics big data language model is used to label the data to be processed, and classification is performed based on the labels. By fine-tuning the big data language model with logistics knowledge, the accuracy and efficiency of data classification are improved.

Benefits of technology

It enables the rapid and accurate classification of interactive data in logistics services, helping relevant personnel understand the opinions of customers, couriers, and customer service staff, thereby improving logistics services.

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Abstract

The invention provides a data classification and model training method and device, a storage medium and a program product, and the method comprises the steps: marking to-be-processed data, namely interaction data in a logistics service, through a logistics big language model, namely a big language model applied to the logistics field, obtaining a label of the to-be-processed data, and then, carrying out the marking of the to-be-processed data; and classifying the to-be-processed data based on the label of the to-be-processed data to obtain a category of the to-be-processed data, the category including at least one of customer opinions, courier opinions and customer service opinions. Therefore, on the basis that the big language model has strong text understanding and generating capabilities, the label of the to-be-processed data can be more accurately determined through the logistics big language model, then the category of the to-be-processed data is determined based on the label, and classification and arrangement of the to-be-processed data can be effectively realized.
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