Idiom Identifier Neutral Text Search
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing text search algorithms fail to identify variations of idioms in electronic text due to differences in punctuation, verb tense, and the addition of modifiers, making it difficult for learners of new languages to understand and recognize idiomatic expressions.
Innovation Solution
The Idiom Identifier converts text to a neutral form, removing punctuation and formatting, and uses an enhanced search algorithm to locate idioms by their key words and relational placement, allowing users to click on identified idioms for definitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a standard text search algorithm is used to search for idioms, then the search is simple and fast, but it fails to identify variations of idioms due to punctuation, verb tense, and modifiers
Solution Approach 1:
The patent segments the idiom matching process into multiple components: converting text to neutral form (removing punctuation, standardizing verbs), segmenting idioms into key components, and separately matching components rather than requiring exact string matches. This segmentation enables identification of idiom variations while maintaining systematic control over the search process
Solution Approach 2:
The patent introduces a neutral text form as an intermediary representation between the original text and the idiom database. This neutral form serves as a mediator that eliminates variations in punctuation, capitalization, and verb tense, allowing the search algorithm to focus on matching key idiom components without being disrupted by superficial textual differences
2Measurement precision
If an enhanced text search algorithm searches for words within close proximity, then it identifies some idiom variations, but it still misses variations with different verb tenses or pronoun forms
Solution Approach 1:
The patent changes the parameters of text representation by converting all text to a neutral form where verb tenses are standardized, pronouns are normalized, and punctuation is removed. This parameter transformation allows the search algorithm to match idioms based on their core semantic components rather than being constrained by grammatical variations
Solution Approach 2:
The patent performs preliminary text normalization before the actual idiom search. By pre-converting the text to neutral form and pre-segmenting idioms into key components, the system prepares the data in advance to enable more accurate and simpler matching during the search operation
3Reliability
If the system marks and defines all idiom variations, then language learning effectiveness improves, but the system complexity and processing time increase
Solution Approach 1:
The patent extracts only the essential key components from each idiom (removing punctuation, standardizing verbs, identifying core nouns and adjectives) to create a simplified representation for matching. This extraction process enables the system to identify idiom variations quickly by comparing only the essential elements rather than processing entire idiom strings
Data Source
AI summary
The “Idiom Identifier” converts an original text document to a “neutral” form containing no punctuation, no capital letters, and having only a single space between each word. Neutral form text also removes hidden markup such as line breaks, paragraph breaks or page breaks. The Idiom Identifier performs an enhanced text search to locate idioms listed in a library file. The Idiom Identifier marks each identified idiom in a marked-up copy of the original text document. A reader can click on the marked-up idiom to see a definition of the idiom.