Multilingual Search Indexing with Sentence-Level Language Analysis
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Solution Overview
Problem
Conventional search systems are inefficient and ineffective when handling multilingual documents, as they either require separate indexing for each language or rely heavily on accurate language detection, leading to misanalysis and resource inefficiency.
Innovation Solution
A multilingual search system that fragments text into sentences using Natural Language Processing, applies language detection to each fragment, and indexes tokens using language-specific analyzers, allowing for a single index and flexible language support.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate search systems are maintained for each language, then language-specific search accuracy is improved, but system complexity and resource consumption increase significantly
Solution Approach 1:
The patent merges multiple language-specific search systems into a single unified search system that can handle multiple languages. Instead of maintaining separate indexing and search infrastructure for each language, the system consolidates these functions while preserving language-specific analysis capabilities through a shared architecture.
Solution Approach 2:
The patent creates a universal search system that can process and search documents in multiple languages through a single interface. The system design allows one search system to perform the functions previously requiring multiple separate systems, achieving multi-functionality without proportionally increasing complexity.
2Productivity
If a single language is used per object, then indexing efficiency is improved, but search effectiveness for multilingual content deteriorates
Solution Approach 1:
The patent segments multilingual documents into language-specific portions or tokens, allowing each segment to be processed with appropriate language analysis. This segmentation enables the system to maintain indexing efficiency by processing segments individually while preserving search effectiveness by ensuring each segment is analyzed with its correct language context.
Solution Approach 2:
The patent applies local quality by using language-specific analysis methods for different portions of the document based on their detected language. Instead of applying a uniform analysis approach throughout, the system adapts the analysis method to match the local language characteristics of each document segment.
3Productivity
If language detection is applied to identify document language, then single-language indexing efficiency is improved, but accuracy deteriorates when document contains multiple languages
Solution Approach 1:
The patent segments the document processing task by detecting language at appropriate granularities (document level, section level, or token level) rather than attempting to identify a single language for the entire document. This allows multilingual documents to be processed as multiple language-specific segments.
Solution Approach 2:
The patent applies partial language detection by identifying languages for only the portions of the document where detection is necessary or reliable, rather than attempting to detect a single language for the entire document. This partial approach avoids the inaccuracies of forced single-language detection while maintaining efficiency.
Data Source
AI summary
System and method for the indexing and searching of multilingual documents are disclosed.