Device-Specific Search Results via Application Rating Segmentation
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Solution Overview
Problem
The increasing diversity of user devices and operating systems complicates the relevance of software application experiences, as applications may perform well on some devices but poorly on others due to hardware and software differences, leading to inconsistent user experiences.
Innovation Solution
A method that receives a search query and a device type identifier from a user device, identifies a consideration set of application records, determines device-specific ratings based on user-provided ratings from similar devices, and generates device-specific search results to provide relevant software applications tailored to the user's device type and operating system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If application search results are generated without device-specific filtering, then the search process is simple and fast, but the relevance of search results to the user's specific device type deteriorates
Solution Approach 1:
The patent segments the application search results by device type, creating separate consideration sets for different device categories (smartphones, tablets, computers, wearables, etc.). This segmentation allows the system to filter and rank applications specifically for each device type, improving relevance without requiring complex manual configuration. The segmentation is implemented through device type identifiers that categorize user devices into predefined groups.
Solution Approach 2:
The patent performs preliminary filtering of application records based on device type before presenting results to the user. By pre-identifying which applications are compatible with and optimized for the user's device type, the system reduces the set of candidate applications in advance. This preliminary action improves search result relevance while keeping the actual search process simple and fast.
2Measurement precision
If device-specific ratings are determined and applied to each application record, then the accuracy of application recommendations improves, but the processing time and computational resources increase
Solution Approach 1:
The patent implements a universal device type classification system that groups diverse devices into common categories (smartphones, tablets, computers, wearables, etc.). This universal categorization allows the system to apply the same rating and filtering logic across all device types, improving recommendation accuracy without requiring device-specific processing for each individual device model. The multi-functional approach handles various device types through a unified framework.
Solution Approach 2:
The patent changes the parameter of application evaluation from generic ratings to device-type-specific ratings. By introducing device type as a key parameter in the rating system, the system can accurately match applications to devices while using efficient pre-computed ratings stored in the application records. This parameter change enables accurate recommendations without real-time computational overhead.
3Reliability
If the system filters application records based on device type identifiers, then the user experience consistency across different devices improves, but the system complexity and data processing requirements increase
Solution Approach 1:
The patent segments the user base by device type identifiers, creating distinct consideration sets for smartphones, tablets, computers, wearables, and other device categories. This segmentation ensures that each user receives application recommendations optimized for their specific device type, improving experience consistency. The segmentation is implemented through simple device type identification and filtering logic.
Solution Approach 2:
The patent introduces device type identifiers as an intermediary between the user's actual device and the application recommendation system. These identifiers act as a mediator that translates diverse device characteristics into standardized categories, enabling consistent treatment of different devices without requiring the system to directly handle the complexity of individual device specifications. The intermediary simplifies the matching process while maintaining reliability.
Data Source
AI summary
A method includes receiving a search query and a device type identifier from a user device at a processing system. The method also includes identifying a consideration set of application records based on the search query. Each application record in the consideration set has an initial score associated therewith indicating a degree to which the application record matches the search query. For each application record, the method includes determining a device-specific rating of the software application identified in the application record based on the device type identifier by the processing system, and determining a result score of the application record based on the device-specific rating and the initial score. The method further includes generating device-specific search results based on the consideration set of application records and the result scores thereof by the processing system and transmitting the device-specific search results from the processing system to the user device.