Structures Maintenance Mapper for Natural Language Service Records
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Solution Overview
Problem
Conventional computer-based solutions are insufficient for efficiently analyzing and searching large sets of natural language text service records related to complex systems, as they struggle with variations in terminology and require repeated queries to account for differences in how systems are described, leading to inefficiencies in computing resources and accuracy.
Innovation Solution
A structures maintenance mapper that clusters terms in natural language service records based on a knowledgebase, associates these terms with a coordinate system, and generates issue maps to facilitate efficient querying and analysis, allowing for the normalization of terms and implicit locations, thereby improving computing efficiency and reducing resource expenditure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional computer-based solutions are used to analyze natural language service records, then the system can process the data, but computing efficiency is low and resource expenditure is high due to repeated queries for terminology variations
Solution Approach 1:
The patent applies preliminary action by pre-clustering terminology variations into normalized terms before queries are executed. The system performs term normalization and clustering in advance, creating a mapping between various terminology expressions and their normalized forms. This preliminary processing eliminates the need for repeated queries to account for terminology differences, thereby improving computing efficiency and reducing resource expenditure during actual service record analysis operations
Solution Approach 2:
The patent introduces an intermediary mechanism in the form of a term clustering module that acts as a mediator between the natural language service records and the analysis system. This intermediary clusters various terminology variations into normalized terms, creating an intermediate layer that translates diverse language expressions into standardized forms. This intermediary processing layer enables efficient querying by eliminating the need to handle terminology variations directly, thus improving productivity while reducing computational resource loss
2Ease of operation
If freeform natural language text is used for service records, then it is simpler for human users to deal with, but computing systems struggle to analyze the data efficiently
Solution Approach 1:
The patent introduces an intermediary term clustering module that bridges the gap between freeform natural language text and computing system analysis. This intermediary processes the natural language service records by clustering terminology variations into normalized terms, enabling computing systems to efficiently analyze the data while preserving the original freeform nature of user inputs. The intermediary layer translates diverse language expressions into standardized forms without requiring users to change their input format
Solution Approach 2:
The patent applies segmentation by dividing the analysis process into distinct stages: first, the system processes and clusters terminology variations in the natural language text; second, it associates clustered terms with coordinate systems; third, it generates issue maps. This segmentation allows the system to handle freeform text efficiently by breaking down the complex analysis task into manageable steps, improving computing productivity while maintaining ease of operation for users
3Reliability
If structured forms are used for service records, then data organization is improved, but it requires specific applications, causes confusion when data are mislabeled, and is unwieldy for end-users
Solution Approach 1:
The patent applies inversion by reversing the traditional approach: instead of requiring users to input data into structured forms, the system automatically processes freeform natural language text and extracts structured information. The term clustering module and issue map generator work backwards from unstructured user inputs to create organized data representations, eliminating the need for users to navigate complex forms while maintaining reliable data organization through automated term normalization and coordinate system association
4Measurement precision
If repeated queries are performed to account for terminology variations, then accuracy is improved, but computing time and resource usage increase
Solution Approach 1:
The patent applies preliminary action by pre-clustering all possible terminology variations into normalized terms before analysis queries are executed. The system creates a comprehensive term clustering structure that maps various language expressions to their normalized forms in advance. This preliminary clustering ensures that when analysis queries are performed, the system can accurately handle terminology variations through the pre-established mappings rather than performing repeated queries, thereby maintaining measurement precision while significantly reducing computing time loss
Solution Approach 2:
The patent uses copying by creating normalized term representations that replicate the meaning of various terminology variations in a standardized format. Instead of performing repeated queries to check for different terminology expressions, the system creates copy mappings between various term variations and their normalized forms. This copying approach preserves analysis accuracy by ensuring all terminology variations are accounted for through pre-created mappings, while eliminating the need for time-consuming repeated queries
Data Source
AI summary
Systems and methods are provided herein for enabling a computing system to search and interact with service records containing natural language text to aid in the analysis of those records by: displaying in a user interface an image of a complex system; receiving, from the user interface, a high-level selection of criteria of the complex system; querying issue maps associated with individual natural language service records of a corpus of natural language service records based on the high-level selection, wherein the issue maps specify at least one term related to the complex system and a location on the complex system associated with the at least one term; and returning at least one issue map, wherein the at least one issue map returned specifies a term or location correlated to the criteria of the complex system indicated by the high-level selection.