Conceptual Associative Protocol for Data Corpus Integrity
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Solution Overview
Problem
Current search technologies fail to effectively identify the conceptual and grammatical coherence of a data corpus, leading to irrelevant search results and user confusion, as they struggle to handle natural language queries efficiently.
Innovation Solution
The implementation of a Conceptual Associative Protocol (CIRN) that analyzes word elements within a data corpus to identify conceptual and grammatical associations, determining the integrity of the data corpus and selecting appropriate search behavior to match its consistency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If current search technologies retrieve documents based on keyword matching, then the search engine can deliver large amounts of data, but the results are not conceptually coherent and fail to match user intent
Solution Approach 1:
The patent segments the search query into individual word elements and analyzes their grammatical roles and associations separately. This allows the system to evaluate conceptual coherence at the element level while maintaining the ability to retrieve comprehensive results, resolving the contradiction between quantity and precision.
Solution Approach 2:
The patent introduces an intermediary integrity analysis layer between the search engine and the data corpus. This intermediary evaluates grammatical integrity and conceptual coherence without preventing comprehensive data retrieval, acting as a mediator that maintains both quantity and precision.
2Measurement precision
If the search engine analyzes grammatical integrity of queries, then the quality of search results improves, but the complexity of the search system increases
Solution Approach 1:
The grammar analysis is segmented into discrete grammatical elements (subject, verb, object, modifiers) that can be independently identified and evaluated. This segmentation simplifies the overall analysis process while maintaining high quality result assessment.
Solution Approach 2:
The patent changes the parameter of analysis from comprehensive sentence-level grammatical analysis to focused identification of key grammatical elements and their associations. This parameter change reduces computational complexity while preserving the ability to assess result quality.
3Measurement precision
If the search engine modifies behavior based on query integrity, then the matching accuracy improves, but the difficulty of detecting and measuring query integrity increases
Solution Approach 1:
The patent transforms the complex task of integrity detection into measurable parameters by identifying specific grammatical elements and their associations. This parameter transformation makes integrity detection systematic and measurable rather than subjective and difficult.
Solution Approach 2:
The patent replaces manual or intuitive integrity assessment with an automated computational system that applies grammatical rules and association analysis. This substitution eliminates the difficulty of manual detection while maintaining high matching accuracy.
Data Source
AI summary
A preferred method for identifying at least one of a grammatical, linguistic and/or conceptual integrity of a data corpus is disclosed. In a preferred method, the associations between several word elements of a data corpus are identified. Then, the word elements experiencing several associations are used for identifying the continuum between associations and the number of word elements involved and/or not involved in the associations which is then used for identifying at least one of a: linguistic, semantic, grammatical, conceptual or other integrity or coherence of the analyzed data corpus, such as a query for optionally displaying a data corpus understanding and/or selecting a particular search behavior or other.