Context-Aware Content Sharing Recommendation System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current content sharing methods require users to manually select content and recipients, leading to inconvenience due to the lack of automated recommendations based on usage history and context.
Innovation Solution
A device and method that recommend services and share targets for content sharing using context information, such as interaction history and situation awareness, to facilitate easier and more intuitive sharing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually select content and recipients for sharing, then content sharing functionality is achieved, but user convenience and ease of operation deteriorate due to the need for individual selection
Solution Approach 1:
The system performs preliminary actions by automatically analyzing user history, device context, and interaction patterns before the sharing operation. It pre-recommends both the content to be shared and the recipient devices, so users only need to confirm rather than manually select each parameter, thereby reducing time and effort
Solution Approach 2:
The system enables self-service by automatically gathering context information from device operations, interaction histories, and situational data. This automated information collection and analysis allows the system to autonomously generate sharing recommendations without requiring manual user input for each sharing instance
2Measurement precision
If the system collects and stores context information from interactions, then recommendation accuracy improves, but device complexity and data management burden increase
Solution Approach 1:
The system applies multi-functionality by using the same context information collection and analysis framework for multiple purposes: recommending content to share, identifying recipient devices, and determining appropriate sharing methods. This universal approach consolidates data management functions and reduces overall system complexity
Solution Approach 2:
The system introduces an intermediary processing layer that automatically collects, standardizes, and analyzes context information from various device interactions. This intermediary layer transforms raw interaction data into structured recommendations, simplifying the complexity of direct data management while improving recommendation accuracy
Data Source
AI summary
A method for sharing content of a device is provided. The method includes receiving, by an inputter, an input of a share command of a selected content, recommending at least one service to share the content among a plurality of services that are available in the device and a share target, and sharing, by a controller, the content with the share target selected through the selected service based on a selection input with respect to the at least one recommended service and the share target.