Device-Specific Recommendation Panel for Reducing User Fatigue
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Solution Overview
Problem
Users face fatigue due to encountering numerous irrelevant content and applications on their diverse electronic devices, leading to a demand for a system that efficiently recommends meaningful content and applications based on the devices they possess.
Innovation Solution
A method and device for providing a recommendation panel that includes recommendation items tailored to each type of device, where a server monitors and analyzes usage information from multiple devices connected under a single account to provide contextually relevant recommendations, using an intelligence engine to infer user interests and preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If content is provided across multiple device types, then content availability increases, but user fatigue increases due to meaningless content
Solution Approach 1:
The patent segments content recommendations by device type (mobile phone, tablet PC, TV, etc.), creating device-specific recommendation panels. The server divides the user's device portfolio into distinct categories and generates tailored content recommendations for each device type based on usage patterns, thereby maintaining content availability while reducing fatigue through relevance.
Solution Approach 2:
The patent applies local quality by customizing recommendation content according to each device's specific characteristics and usage context. Different device types receive different content types and recommendation strategies - for example, mobile devices may receive news and messaging content while TVs receive video content. This localized approach ensures content meaningfulness while preserving versatility.
2Measurement precision
If recommendation system analyzes multiple devices, then recommendation accuracy improves, but system complexity increases
Solution Approach 1:
The patent implements a universal server architecture that handles multiple device types through a single multi-functional system. The server performs authentication, usage pattern analysis, and content recommendation across diverse devices using a unified approach. This universal design improves recommendation accuracy by leveraging cross-device data while avoiding the complexity of separate specialized systems for each device type.
Solution Approach 2:
The server acts as an intermediary between multiple devices and the content delivery system. It consolidates usage information from various devices, processes this data centrally to infer user interests, and generates device-specific recommendations. This intermediary approach simplifies the overall system architecture while enhancing recommendation precision through comprehensive data analysis.
Data Source
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AI summary
A method and device which provide a recommendation to a user based on the type of device are provided. The device includes: a user input which is configured to receive a user touch input, a communicator which is configured to transmit a recommendation item request including identification information of the device to a server in response to the user touch input and receive at least one recommendation item selected based on the identification information of the device from the server; a display which is configured to display a recommendation panel including the received at least one recommendation item; and a controller which is configured to control the communicator to receive the at least one recommendation item and control the display to display the recommendation panel.