Weighted Language Resource Selection for Multilingual Devices
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Solution Overview
Problem
Current computing devices face challenges in selecting suitable resources from a resource set based on user language preferences, as they often lack precise matching resources, fail to consider language variants, and do not adequately account for compatibility with applications, leading to suboptimal resource selection.
Innovation Solution
The device calculates weights for selected languages based on their suitability for the resource request, generates a selection order, and presents resources accordingly, allowing for adjustments based on user and application-specific logic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the device selects resources based on exact language matching, then the precision of language match is improved, but the adaptability to language variants and multilingual users deteriorates
Solution Approach 1:
The patent changes the selection parameter from exact language matching to a weighted scoring system that considers multiple factors including language match quality, resource quality, and compatibility. This allows the system to adapt to language variants by assigning appropriate weights rather than requiring exact matches.
Solution Approach 2:
The patent creates a composite selection criterion that combines multiple attributes (language matching, resource quality, compatibility) into a unified weighted score. This composite approach enables the system to handle both exact matches and variants effectively by integrating multiple considerations.
2Adaptability or versatility
If the device considers multiple language variants and compatibility factors, then the adaptability is improved, but the complexity of the selection process deteriorates
Solution Approach 1:
The patent transforms the complex multi-criteria selection problem into a weighted scoring system where each criterion (language match, resource quality, compatibility) is assigned a weight. This parameterization simplifies the decision process by providing a clear mathematical framework for comparing alternatives.
Solution Approach 2:
The patent divides the resource selection process into distinct components: language matching evaluation, resource quality assessment, compatibility checking, and weighted score calculation. This segmentation makes each sub-task manageable and allows independent optimization of each component.
3Ease of operation
If the device uses a simple selection method, then the ease of operation is improved, but the accuracy of resource selection deteriorates
Solution Approach 1:
The patent implements a self-service selection mechanism where the system automatically calculates weighted scores and selects the best resource without requiring manual intervention. This maintains ease of operation while improving accuracy through systematic evaluation of multiple criteria.
Solution Approach 2:
The patent introduces weighted parameters for different selection criteria, transforming a simple selection process into a more accurate multi-factor evaluation. The weighted scoring system automatically balances multiple considerations without requiring complex user configuration.
Data Source
AI summary
A device may be configured to enable a user to select a language, and may fulfill resource requests from applications by selecting, from among resources respectively associated with a language, a resource associated with the selected language of the user. However, this resource selection process may be inadequate if the user selects multiple languages; if a resource associated with the selected language of the user is unavailable, but resources associated with related languages are available; or if the user and/or the application specifies an ordering for the selection among the languages. Presented herein are techniques for performing the resource selection by, for respective languages selected by the user, calculating a weight representing a suitability of the language for the resource request; generating a selection order of the selected languages according to the weights; and selecting a resource based on the position of the associated language in the selection order.