Translation Request Prioritization for Throttling-Aware Queue Management
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Solution Overview
Problem
Conventional translation systems face inefficiencies in handling large volumes of data, leading to increased costs, management complexity, performance issues, and difficulty in predicting costs accurately for large-scale translation projects, with static approaches failing to adapt to fluctuating data volumes and causing throttling when translation requests exceed certain thresholds.
Innovation Solution
A dynamic scenario calculator prioritizes translation requests based on attributes such as contextual information, frequency, size, and language configuration, assigning weights to determine a weighted score for ranking and optimizing the transmission of requests to a data translation engine, allowing for a custom solution that adapts to the expected rate and size of translation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If translation requests are handled in conventional static order, then system simplicity is maintained, but translation service efficiency deteriorates due to throttling and inability to adapt to fluctuating data volumes
Solution Approach 1:
The patent implements dynamic prioritization of translation requests based on multiple attributes including data size, translation language pair, contextual information, and urgency. The system calculates priority scores dynamically for each incoming request and adjusts processing order accordingly, allowing the translation service to adapt to fluctuating data volumes and characteristics rather than using static FIFO processing
Solution Approach 2:
The system changes the processing parameters by introducing a priority scoring mechanism that evaluates multiple attributes of each translation request. Instead of processing requests in a fixed order, the system transforms the processing approach by calculating composite priority scores based on data size, language pair complexity, contextual urgency, and other factors, thereby optimizing translation service efficiency
2Productivity
If infrastructure is scaled to handle large volumes of translation requests, then translation capacity is improved, but costs increase and management complexity increases
Solution Approach 1:
The patent changes the approach to handling large volumes by introducing parameter-based prioritization instead of uniform processing. The system evaluates multiple parameters including data size, language pair, contextual information, and urgency to dynamically adjust processing order. This allows the existing infrastructure to handle variable workloads efficiently without requiring proportional scaling, thereby reducing management complexity and costs
3Productivity
If all translation requests are processed equally, then fairness is maintained, but translation service efficiency deteriorates due to inability to prioritize urgent or important requests
Solution Approach 1:
The patent applies local quality by treating different translation requests differently based on their specific attributes. Instead of uniform processing, the system evaluates each request's data size, language pair complexity, contextual information, and urgency to assign appropriate priority levels. This ensures that urgent or important requests receive preferential processing while maintaining fair treatment based on objective criteria
4Reliability
If translation requests are queued in static order, then system simplicity is maintained, but translation quality deteriorates due to throttling when requests exceed certain thresholds
Solution Approach 1:
The patent implements dynamic queue management by calculating priority scores for each incoming translation request based on multiple attributes including data size, language pair, contextual information, and urgency. The system dynamically adjusts the processing order based on these priority scores, allowing urgent requests to bypass the standard queue and be processed immediately, thereby preventing throttling and maintaining translation quality
Data Source
AI summary
The present disclosure provides a method and system for prioritizing translation requests in a translation service system. The method comprises receiving the one or more translation requests from the one or more users. The method further comprises extracting one or more attributes associated with the one or more translation requests, wherein the one or more attributes include at least one of: contextual information, frequency, size and language configuration of the one or more translation requests. The method further comprises assigning a weight to each attribute of the one or more translation requests. The method further comprises calculating a weighted score for the one or more translation requests based on the assigned weight to each attribute of the one or more attributes and ranking the one or more translation requests based on the weighted score. The method further comprises transmitting the one or more translation requests based on the rank to a data translation engine for translation. A system for prioritizing translation requests is also disclosed.