Multi-Language Document Indexing via NLP Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current document management systems face challenges in accurately indexing and searching documents in multiple languages, leading to incomplete indexing and unfindable documents due to manual language selection errors and system defaults.
Innovation Solution
A method and system that automatically determine the document language by analyzing the document with a natural language processing service and indexing it based on the organization's language and the document's primary language, ensuring accurate search results across multiple languages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual language selection is used for imported documents, then users can control the indexing language, but the process is time consuming and prone to errors
Solution Approach 1:
The system performs automatic language detection on imported documents using NLP services, eliminating the need for manual language selection by users. The document itself 'services' the language identification function through automated analysis, resolving the contradiction between accuracy and time consumption.
Solution Approach 2:
The manual mechanical process of user language selection is replaced with an automated NLP-based language detection system. This substitution eliminates human error and time consumption while maintaining or improving language identification accuracy through algorithmic analysis.
2Productivity
If default languages are set for imported documents, then the system can quickly index documents, but this creates inherent bias toward default languages resulting in over proliferation of documents indexed in the default language
Solution Approach 1:
The system performs preliminary language detection analysis on imported documents before final indexing, using NLP services to identify the actual document language. This preliminary action prevents premature indexing in default languages while maintaining efficient processing through automated analysis.
Solution Approach 2:
The system dynamically changes the indexing language parameter based on NLP analysis results rather than statically using default language settings. This parameter adaptation allows the system to maintain high indexing speed while accurately reflecting the actual document language.
3Ease of operation
If simple default language settings are used, then the system is easy to operate, but documents with multiple languages are not properly indexed
Solution Approach 1:
The NLP-based language detection system provides universal language identification capability that handles both single-language and multi-language documents. The system automatically detects and indexes multiple languages within a single document, extending the simple default setting functionality to handle complex multi-language scenarios without requiring user intervention.
Data Source
AI summary
A method of optimizing full text search results for multiple languages includes importing a document from a first organization including one or more first organization users, wherein the one or more first organization users are associated with a first organization location; determining a first organization language based on the first organization location; analyzing the imported document with a natural language processing (NLP) service to determine a primary document language; and indexing a determined document language to the imported document based at least in part on the first organization language and the primary document language, wherein indexing the determined document language to the imported document causes the document to be searched using a document search tool in the determined document language.