Language Detection in Short Communications via Line Cache Assembly
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Solution Overview
Problem
Existing language detection algorithms are ineffective for short communications, as they require a threshold length of well-formed text to accurately identify languages, and fail to detect languages in short communications with non-standard formats or multiple languages in conversations.
Innovation Solution
The method enhances language detection by artificially lengthening short communications and using a line cache to assemble compound text for analysis, allowing for improved language identification and detection of multiple languages in conversations, even when the text is not well-formed or of standard length.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing language detection algorithms are used on short communications, then the detection process is simple and fast, but the language detection accuracy is low due to insufficient text length
Solution Approach 1:
The patent segments the language detection process into multiple stages: individual short message analysis, compound text assembly from multiple messages, and iterative detection cycles. This segmentation allows the system to progressively build sufficient text for accurate detection while maintaining manageable process complexity through modular implementation.
Solution Approach 2:
The patent applies preliminary action by pre-assembling compound text from multiple short communications before performing language detection. This preliminary text assembly creates sufficient content for accurate algorithm analysis, resolving the contradiction between simple processing and detection accuracy.
2Reliability
If language detection is performed on each short communication individually, then the processing time is short, but the language detection confidence level is low
Solution Approach 1:
The patent implements continuous useful action through iterative detection cycles that process messages as they arrive, continuously updating compound text and re-evaluating language detection confidence. This continuous process maintains high reliability by accumulating sufficient data over time while minimizing total processing time through incremental updates rather than waiting for complete data sets.
Solution Approach 2:
The system performs preliminary assembly of compound text from multiple short communications before detection, creating a more robust text base that improves confidence levels without requiring excessive waiting time, as the assembly occurs in the background as messages are received.
3Measurement precision
If compound text is assembled from multiple short communications to improve detection accuracy, then the language detection accuracy improves, but the processing complexity increases
Solution Approach 1:
The patent segments the text assembly process into manageable components: individual message storage in a queue, systematic compound text construction from queued messages, and modular detection algorithms. This segmentation reduces processing complexity by breaking down the complex task of handling multiple languages and formats into discrete, manageable operations.
Solution Approach 2:
The patent creates a universal processing framework that handles multiple languages, formats, and message types through a single compound text assembly mechanism. This multi-functional approach reduces overall system complexity by providing a unified solution rather than requiring separate processing paths for different scenarios.
4Reliability
If the language detection algorithm requires well-formed text of threshold length, then the detection reliability is high, but it fails to detect languages in short communications with non-standard formats
Solution Approach 1:
The patent applies preliminary text processing and normalization to convert non-standard short communication formats into well-formed compound text before detection. This preliminary action preserves detection reliability by ensuring the algorithm receives properly formatted input while enhancing adaptability through the preprocessing stage that handles various message formats, abbreviations, and linguistic variations.
Solution Approach 2:
The system implements a universal text normalization framework that handles multiple message formats, languages, and linguistic styles through a single processing pipeline. This multi-functional approach maintains high detection reliability across diverse non-standard formats by providing consistent preprocessing that adapts to various input types.
Data Source
AI summary
A method, system, and computer usable program product for enhancing language detection in short communications are provided in the illustrative embodiments. A short communication is stored in an element of a line cache. The line cache is accessible to an application executing in a data processing system. The element is an element in a set of elements in the line cache. A compound text is assembled from contents of a subset of the elements of the line cache. A language identifier (language ID) is received for the compound text from a language detection algorithm. The language ID is stored in a language cache element of a language ID cache. The language ID cache is accessible to the application and includes a set of language cache elements. A language of the short communication is determined using the contents of a subset of language cache elements.