Image Keyword Extraction for Ad Selection
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Solution Overview
Problem
Disparate computing resources face challenges in efficiently processing and accurately parsing image or audio-based instructions due to differences in voice models, leading to inefficient information transmission and processing, particularly in scenarios where network traffic data is excessive and bandwidth utilization is suboptimal.
Innovation Solution
A system that receives images captured by a user's device, analyzes them to identify keywords, and uses these keywords to select and present relevant ads by comparing them with ad keywords, incorporating scoring weights that decrease with the age of the image keywords, thereby improving ad selection and presentation efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image keywords are used to identify candidate ads, then ad selection accuracy is improved, but network transmission load increases
Solution Approach 1:
The system performs preliminary image analysis to extract keywords and stores them for future ad selection processes. By pre-processing images and extracting relevant keywords before ad requests are made, the system reduces the need for repeated network transmissions of raw image data, thereby improving ad selection accuracy while controlling network load.
Solution Approach 2:
The system extracts only the essential keyword information from images rather than transmitting or processing the entire image data. This extraction approach captures the semantic content needed for accurate ad selection while significantly reducing the quantity of data that needs to be transmitted over the network.
2Measurement precision
If image analysis is performed to identify keywords, then user intent inference accuracy is improved, but processing time increases
Solution Approach 1:
The system performs image analysis and keyword extraction in advance, before actual ad selection is needed. By pre-processing images and storing extracted keywords, the system maintains high user intent inference accuracy while reducing processing time during live ad selection operations.
Solution Approach 2:
The system dynamically adjusts the depth and complexity of image analysis based on available resources and time constraints. For time-critical operations, it uses pre-extracted keywords, while for non-critical operations, it performs more comprehensive analysis, thereby balancing accuracy with processing time.
3Measurement precision
If scoring weights are applied to image keywords based on age, then ad selection relevance is improved, but system complexity increases
Solution Approach 1:
The system changes the parameter of keyword scoring by introducing time-based weight decay. Older keywords are automatically assigned lower weights while recent keywords receive higher weights, allowing the system to adapt to changing user interests without requiring complex manual reconfiguration. This simple parameter change effectively improves ad selection relevance.
Data Source
AI summary
Systems and methods of selecting content based on image data are provided. A system can receive an image captured by a camera of the computing device. The system can analyze the image to identify a pattern that matches a predetermined pattern of an object stored in an image pattern database comprising a plurality of predetermined patterns of objects. The system can identify one or more image keywords from the image based on the predetermined pattern of the object that matches the image. The system can select, based on a comparison of the one or more image keywords with one or more keywords of each of a plurality of content items, a content item. The system can provide, to the computing device, the content item to cause the computing device to present the content item.