SNS Image Evaluation Apparatus Using Trending Pattern Analysis
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Solution Overview
Problem
Users face a burden in selecting images for social networking services (SNS) that are likely to receive positive evaluations, as existing technologies do not effectively reduce the effort required to determine trending images over time.
Innovation Solution
An image evaluation apparatus that obtains and analyzes posted data from SNS, generates parameters based on image analysis, stores and associates evaluation values, and calculates parameter evaluation values to notify users of image evaluation variations over time, helping to determine which images are likely to receive positive evaluations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users visually check trending images on networking services to select images for posting, then they can identify images likely to receive positive evaluation, but the user burden and time required increase significantly
Solution Approach 1:
The patent replaces the manual visual checking process with an automated image analysis system that uses computer vision and machine learning algorithms to evaluate images based on trending patterns, thereby eliminating the need for users to manually review numerous images while maintaining accurate selection capability
Solution Approach 2:
The system enables automated self-evaluation of images by analyzing image features, comparing them against trending data, and automatically determining which images are likely to receive positive evaluations, freeing users from the manual selection process
2Reliability
If users manually evaluate multiple images to determine which will receive positive feedback, then they can make informed posting decisions, but the operational complexity and effort increase
Solution Approach 1:
The patent substitutes manual image evaluation with an automated system that applies machine learning models trained on historical posting data and user feedback, providing reliable evaluation predictions without requiring user effort in analyzing multiple images
Solution Approach 2:
The system introduces an intermediary image analysis apparatus that acts as a mediator between the user and the networking service, automatically evaluating images and providing recommendations, thereby shielding users from the complexity of manual evaluation while maintaining high reliability
3Measurement precision
If the system analyzes image features and compares them with trending data to predict positive evaluations, then selection accuracy improves, but the device complexity increases
Solution Approach 1:
The patent divides the image evaluation system into distinct functional modules: image acquisition module, feature extraction module, trending data analysis module, and evaluation prediction module. This segmentation allows each module to perform a specific function, improving accuracy while managing complexity through modular design
Solution Approach 2:
The image analysis apparatus is designed with multi-functional capabilities, including image feature extraction, trending pattern recognition, evaluation prediction, and automated posting recommendations, allowing a single system to handle multiple tasks that would otherwise require separate systems
Data Source
AI summary
An image evaluation apparatus which is capable of evaluating an image that can be given positive evaluations in a networking service. Images included in post data posted on a networking service and evaluating values for the post data are obtained at predetermined time intervals. When the post data has been obtained, first parameters are generated by applying an image analysis process to the images. The first parameters and the evaluation values are stored in association with each other. Upon input of image to be evaluated, a second parameter is generated by applying the image analysis process to the image to be evaluated. A first parameter corresponding to the second parameter is extracted from the plurality of stored first parameters. Parameter evaluation values representing variations in the evaluation values associated with the extracted first parameter in notifying order are calculated. Notification of the calculated parameter evaluation values is provided.