Advertisement Material Selection Using Value Estimation Models
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Solution Overview
Problem
Existing advertisement generation methods lack rationality and fail to ensure delivery effectiveness, often leading to inefficient use of resources and reduced revenue due to manual generation methods that do not align with actual needs or external advertisement delivery systems.
Innovation Solution
An advertisement generation method that estimates advertisement values using a value estimation model, searches for target materials to satisfy specific requirements, and generates advertisement plans to optimize delivery effectiveness, utilizing machine learning techniques to ensure alignment with actual needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual advertisement generation methods are used, then ease of operation is maintained, but delivery effectiveness and rationality deteriorate
Solution Approach 1:
The system performs self-service by automatically generating advertisement plans through the determination module and generation module. The computer automatically determines material sets, estimates advertisement values, searches for target materials, and generates advertisement plans without manual intervention, thereby improving delivery effectiveness while maintaining operational simplicity through automation.
Solution Approach 2:
The patent replaces manual mechanical operations with an automated computer-based system. The determination module, generation module, and value estimation model work together to substitute human manual generation processes with automated computational methods, enhancing both reliability and efficiency.
2Manufacturing precision
If automated value estimation and material search are implemented, then advertisement plan rationality improves, but device complexity increases
Solution Approach 1:
The system is segmented into distinct functional modules: a determination module for determining material sets and estimating values, a generation module for generating advertisement plans, and a value estimation model. This segmentation allows each module to perform its specific function with high precision while managing overall system complexity through modular architecture.
Solution Approach 2:
The value estimation model serves as an intermediary between the determination module and the generation module. It processes material information and provides estimated advertisement values that guide the selection of target materials, thereby improving plan rationality while managing complexity through this intermediate processing layer.
3Reliability
If multiple target materials are searched and selected, then advertisement value satisfaction improves, but loss of time increases
Solution Approach 1:
The system performs preliminary action by pre-determining material sets and pre-estimating advertisement values before generating advertisement plans. The determination module prepares candidate materials and their estimated values in advance, allowing the generation module to quickly select target materials that satisfy advertisement value requirements, thereby reducing overall processing time.
Solution Approach 2:
The value estimation model provides feedback on the estimated advertisement values of candidate materials. This feedback mechanism allows the system to efficiently identify and select target materials that satisfy the required advertisement values without exhaustively searching all possible materials, thus reducing search time while maintaining high satisfaction rates.
Data Source
AI summary
This application provides a method for generating an advertisement, a computing device, a computer storage medium, and a computer program product. The method comprises: determining a material set; obtaining at least one estimated advertisement value generated by an advertisement plan based on a material in the material set; searching for a plurality of target materials such that at least one estimated advertisement value, respectively generated by a plurality of advertisement plans based on the plurality of target materials, satisfies an advertisement value requirement; and generating the plurality of advertisement plans by utilizing the plurality of target materials. The technical solution provided in this application ensures the rationality of advertisement plan generation.