Query Language Filter for Cross-Language Retrieval
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Solution Overview
Problem
Search engines often return few or irrelevant results for queries in less popular languages, and automatic translation is computationally expensive, making it desirable to determine when translation is unnecessary to avoid unnecessary translation costs.
Innovation Solution
A method where a search server system receives a search query and determines the application language, translating the query only if certain filter criteria are met, such as a low probability that the query is in the application language, and conveys relevant results to the client system, thereby avoiding unnecessary translation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automatic translation is applied to all search queries, then search results relevance for non-English queries is improved, but computational expense increases
Solution Approach 1:
The system changes the parameter of translation application from universal to selective based on language identification probability thresholds. By adjusting the probability threshold parameter, the system optimizes between translation accuracy and computational resource consumption, only translating queries where the detected language differs significantly from the target language with high confidence
Solution Approach 2:
The system uses language identification algorithms to automatically determine whether translation is necessary, eliminating the need for manual configuration or user specification. The self-service mechanism analyzes query characteristics and autonomously decides on translation based on predefined criteria, reducing unnecessary computational overhead
2Use of energy by moving object
If translation is avoided for queries already in the target language, then computational expense is reduced, but search results relevance may deteriorate if language misidentification occurs
Solution Approach 1:
The system performs preliminary language identification and probability assessment before executing the search and translation processes. By conducting this preliminary analysis, the system可以避免 unnecessary translation operations while ensuring that queries requiring translation are properly handled, thus optimizing both computational efficiency and result accuracy
Solution Approach 2:
The system uses probability factors from language identification as feedback to control the translation process. When the probability indicates high confidence that the query is already in the target language, the system feedback-loops to skip translation, thereby reducing computational expense while maintaining reliability through confidence-based decision making
Data Source
AI summary
A method of processing search queries, performed by a search server system, includes receiving, from a client system, a search query and an indicia of an application language associated with an application used at the client system to perform the search query. The search server system responds by identifying a first language and a first probability factor that specifies a likelihood that the search query is in the first language. In response to satisfaction of filter criteria, comprising a determination that the first language corresponds to the application language, the search server system translates the search query to a translated search query in a second language distinct from the application language, obtains search results for the translated search query, and conveys to the client system at least a subset of the search results for the translated search query.