Marketing business configuration method and device, storage medium, equipment and product
By combining semantic parsing of user dialogue information with rule and preference bases, marketing business configuration information is automatically generated, solving the problem of low efficiency in manual configuration and achieving efficient and accurate marketing resource management.
CN122045272APending Publication Date: 2026-05-15ANT BLOCKCHAIN TECHNOLOGY (SHANGHAI) CO LTD
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Patent Information
- Application Number
- CN202610117362.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-01-27
- Publication Date
- 2026-05-15
AI Technical Summary
Technical Problem
The current marketing configuration method relies on manual operation, which leads to low configuration efficiency and is prone to errors, affecting marketing results and increasing the company's operating costs and decision-making risks.
Method used
By acquiring user dialogue information and performing semantic parsing to determine business scenario information, matching configuration information is generated using a configuration rule base and a historical preference base to achieve automated configuration.
Benefits of technology
It improved the efficiency and accuracy of marketing operations, optimized the effectiveness of marketing resource allocation, and reduced corporate operating costs and decision-making risks.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention provides a marketing business configuration method and device, a storage medium, equipment and a product. The method comprises the steps of obtaining dialogue information input by a user for a marketing service, and performing semantic analysis on the dialogue information to determine service scene information corresponding to the marketing service; according to the business scene information, determining a target configuration rule required for configuring the marketing business in a preset configuration rule library, and determining historical configuration preference information matched with the business scene information in a historical preference library of the user; and under an information generation mode and constraint conditions specified by the target configuration rule, through a preset configuration recommendation model, generating configuration information matched with the historical configuration preference information and suitable for the marketing business.
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