Personalized Image Filter Recommendation via User Activity Analysis
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Solution Overview
Problem
Existing image editing technologies on electronic devices provide limited and standardized image effect filters, failing to meet users' personal preferences.
Innovation Solution
An electronic device with a communication circuit, camera, memory, and processor determines user preferences based on operation history and recommends or provides image effect filters from external devices or internal memory during image editing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If standardized image effect filters are provided by application developer or electronic device manufacturer, then the image editing function is available, but the type of image effect filter is limited and may not meet user's personal taste
Solution Approach 1:
The system performs preliminary actions by analyzing user activity history before the user needs image editing, determining user preferences in advance, and preparing personalized filter recommendations. This allows the system to have diverse filter options ready when the user initiates editing, resolving the contradiction between filter variety and system complexity.
Solution Approach 2:
The system enables self-service by automatically analyzing user behavior patterns and generating personalized filter recommendations without requiring manual user configuration. The electronic device autonomously determines user preferences from operation history and provides tailored filter selections, achieving adaptability while maintaining simple user interaction.
2Adaptability or versatility
If user activity history is analyzed to determine user preferences, then personalized filter recommendations can be provided, but additional processing and data management are required
Solution Approach 1:
The processor performs multiple functions using the same data processing infrastructure: it handles user activity history analysis, determines user preferences, and generates filter recommendations all through a unified processing system. This multi-functional approach achieves personalization capability while avoiding the need for separate complex subsystems for each function.
Solution Approach 2:
The system introduces an intermediary layer of preference determination that mediates between raw user activity data and final filter recommendations. This intermediary processing step transforms complex user behavior data into simplified preference profiles, which then guide filter selection without requiring direct complex analysis at the recommendation stage.
Data Source
AI summary
An embodiment of the present invention provides an electronic device comprising: a communication circuit; at least one camera device; a memory; a display; and a processor electrically connected to the communication circuit, the at least one camera device, the memory, and the display. The processor is configured to: determine a query on the basis of a user activity related to operation of the electronic device; confirm whether or not at least one external device connected through the communication circuit or the memory comprises an image effect filter corresponding to the query; acquire the image effect filter corresponding to the query from the at least one external device or the memory when it is confirmed that the at least one external device connected through the communication circuit or the memory comprises the image effect filter corresponding to the query; output an image taken by the at least one camera device through the display; and provide the acquired image effect filter when an event related to editing of the output image occurs. In addition, various embodiments recognized through the specification are possible.