Automated Advertisement Characteristic Extraction and Filtering
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Solution Overview
Problem
Current advertisement detection methods are inefficient due to the need for manual extraction and updating of advertisement characteristics, leading to low accuracy and timeliness in detecting new or modified advertisements in application programs.
Innovation Solution
An automated method for extracting and filtering characteristics from advertisement samples to determine advertisement probabilities, allowing for rapid updates and accurate detection of new advertisements without manual processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual extraction of advertisement characteristics is used, then detection accuracy can be maintained for known advertisements, but detection efficiency and timeliness deteriorate when new advertisements appear
Solution Approach 1:
The system automatically extracts advertisement characteristics from application programs without manual intervention. The characteristic extraction module autonomously identifies and extracts features from ad samples, and the characteristic value determination module automatically calculates probability values, enabling the system to self-update detection capabilities for new advertisements while maintaining accuracy.
Solution Approach 2:
The system performs preliminary extraction of advertisement characteristics from multiple ad samples and pre-calculates characteristic values before actual detection is needed. By preparing characteristic data in advance and storing it in a database, the system ensures rapid and accurate detection when new advertisements appear, eliminating the need for manual updates at detection time.
2Adaptability or versatility
If manual updating of advertisement characteristics is performed, then detection can adapt to new advertisements, but the time required for updates increases
Solution Approach 1:
The system automatically adapts to new advertisements by autonomously extracting characteristics from new ad samples and updating the characteristic database without manual intervention. This self-updating mechanism ensures continuous adaptability to evolving advertisement formats while eliminating time losses associated with manual characteristic updates.
Solution Approach 2:
The system implements a feedback mechanism where detection results and new ad samples are continuously fed back into the characteristic extraction and value determination modules. This closed-loop feedback enables automatic refinement and updating of advertisement characteristics, improving adaptability over time without requiring manual updates.
3Speed
If automated characteristic extraction is implemented, then detection speed and timeliness improve, but system complexity increases
Solution Approach 1:
The system divides the automated characteristic extraction process into distinct modular components: the characteristic extraction module, the characteristic value determination module, and the matching module. Each module performs a specific function independently, which simplifies the overall system architecture while maintaining high detection speed and automating the entire characteristic extraction workflow.
Data Source
AI summary
A device extracts a plurality of characteristics from a sample set. For each extracted characteristic, the device determines different types of advertisements carried in advertisement samples in the sample set matching the characteristic. The device determines characteristic values of the characteristic that correspond to the different types of advertisements. The device filters based on characteristic values of the characteristic that correspond to the different types of advertisements, the extracted plurality of characteristics to obtain respective advertisement characteristics of the different types of advertisements. The device matches the advertisement characteristics of the different types of advertisements against characteristics extracted from a to-be-detected sample, and determines whether the to-be-detected sample carries an advertisement, and if so, which type of advertisement.