Network Service Advertisement Targeting via User Selection
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Solution Overview
Problem
Existing network service platforms face challenges in effectively presenting targeted advertisement information to users without invading user privacy and efficiently utilizing computing resources.
Innovation Solution
A method and system that allows users to select options on a user interface, which are recorded and used to query for matching advertisements, reducing the need for extensive data analysis and resource usage, and avoiding privacy invasion by allowing users to actively choose advertisement types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If user Internet surfing records are collected and analyzed to obtain user attribute information for targeted advertising, then advertising targeting accuracy is improved, but computing resources and storage resources are heavily occupied, requiring complex software and hardware devices with high implementation cost
Solution Approach 1:
The patent extracts only the essential advertising type information that users actively select, separating it from the complex mass of user surfing records. This extraction approach obtains sufficient targeting data without requiring extensive data collection and analysis infrastructure, thereby reducing device complexity while maintaining advertising accuracy.
Solution Approach 2:
Instead of analyzing user behavior data to infer advertising preferences (traditional approach), the patent inverts the process by directly obtaining advertising type selections from users. This inversion eliminates the need for complex data mining and computing resources, achieving accurate targeting with simpler systems.
2Measurement precision
If user Internet surfing records are analyzed through data mining and computing to obtain user attributes, then targeted advertising is achieved, but a large number of computing resources and storage resources are occupied
Solution Approach 1:
The patent extracts directly the advertising type information users actively select, obtaining precise user preferences without requiring energy-intensive data mining and computing processes. This extraction method achieves accurate user attribution with minimal computing resource consumption.
Solution Approach 2:
The patent uses simple, easily obtainable user selection data instead of requiring expensive and complex data analysis infrastructure. The approach uses minimal processing resources to achieve the desired targeting accuracy, effectively replacing expensive computing resources with simpler alternatives.
3Loss of information
If extensive data mining and analysis of user surfing records are performed, then comprehensive user attribute information is obtained, but implementation cost increases and user privacy information may be invaded
Solution Approach 1:
The patent extracts only the specific advertising type information that users actively select, obtaining necessary user preference data without requiring extensive collection and analysis of sensitive user surfing records. This approach achieves sufficient information completeness for advertising targeting while minimizing privacy invasion.
Solution Approach 2:
The patent enables users to actively provide their own advertising type preferences through selection operations. This self-service approach allows users to control what information is shared, obtaining complete advertising targeting information without requiring the system to invade user privacy through extensive data mining.
Data Source
AI summary
Options are displayed on a user interface that provides a network service, a selection instruction of a user is received, and an option selected by the user is acquired according to the selection instruction; the option selected by the user is recorded; and an advertisement that matches the option is queried for, and the advertisement is presented to the user.