Browser Multilanguage Tokenizer for Compact Text Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Implementing text segmentation across multiple languages in a web browser environment is challenging due to size and compatibility limitations, as traditional libraries and toolkits exceed browser constraints and are not universally compatible.
Innovation Solution
A heuristic-based multilanguage tokenizer that operates within web browser constraints by employing rule paradigms for different character types, handling diacritics, emojis, and script boundaries to segment text effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional text segmentation libraries are used, then text segmentation accuracy is improved, but binary size increases beyond browser constraints
Solution Approach 1:
The patent extracts and implements only the essential tokenization logic needed for multilingual text segmentation, removing dependencies on large third-party libraries. The tokenizer uses native JavaScript implementations of segmentation algorithms that work directly in the browser without requiring external library files, thus reducing binary size while maintaining segmentation functionality.
Solution Approach 2:
The patent implements a simplified copy of the essential tokenization functionality directly within the browser environment, rather than relying on external library copies. This involves recreating the core segmentation logic using native browser-supported methods, eliminating the need to include large library files in the browser bundle.
2Adaptability or versatility
If third-party tokenization libraries are integrated, then text segmentation capability is improved, but compatibility across different browsers deteriorates
Solution Approach 1:
The patent creates a universal tokenizer that works across all major browsers by implementing segmentation logic using only standard JavaScript features and Unicode properties that are universally supported. The solution avoids browser-specific APIs and implements fallback mechanisms to ensure consistent behavior across different browser environments, making the text segmentation capability universally applicable.
3Adaptability or versatility
If comprehensive language support is implemented, then text segmentation coverage is improved, but processing complexity increases
Solution Approach 1:
The patent applies different segmentation strategies tailored to specific language characteristics and script types. The tokenizer detects the script type (Latin, Cyrillic, Arabic, Hebrew, etc.) and applies appropriate segmentation rules for each, rather than using a single complex algorithm for all languages. This localized approach reduces overall processing complexity while maintaining comprehensive language support.
Data Source
AI summary
Methods, systems, and storage media for providing a heuristic multilanguage tokenizer in a web browser environment are disclosed. Exemplary implementations can receive a query; generate a query set comprising at least one query token; generate a result set from a searchable phrase, wherein the result set comprises at least one phrase token; generating at least one supplemental set. Determining that any of the sets comprise at least one of: a first character-type, a second character-type, or an emoji. In response to determining the first character-type: determining a word boundary and extracting a diacritic. In response to determining that the query, result set and the supplemental set comprise the second-type or the emoji, adding a space around each second character-type or emoji in the set; and segmenting the set into a plurality of tokens.