NLP Data Analysis System for Automated Theme Extraction
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Solution Overview
Problem
Manual processing of large data files is time-consuming and prone to bias, as users must manually read and analyze potentially unfamiliar data formats, which can take weeks and is susceptible to focusing on specific types of information.
Innovation Solution
An automated system using natural language processing (NLP) to analyze data files by identifying trending themes through Ngrams, sorting results by length, and filtering out extraneous information, allowing for the derivation of themes from column and cell-based data formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual processing is used to analyze data files, then users can understand and evaluate the data, but the processing time increases significantly and bias is introduced
Solution Approach 1:
The patent introduces an automated analysis system as an intermediary between the data file and the user. This system includes a processor that executes instructions to automatically read, parse, and analyze data files, generating analytical results without requiring manual user intervention. The intermediary system eliminates the trade-off by providing both speed (automated processing) and accuracy (consistent application of analysis rules) simultaneously.
2Loss of information
If manual reading of data files is performed, then users can deduce information from text entries, but the effort and time required increase for large and complicated files
Solution Approach 1:
The patent replaces the mechanical system of manual reading and analysis with an automated computational system. The processor automatically reads data files, parses text entries, identifies patterns, and extracts information using programmed algorithms. This substitution eliminates the time-consuming manual process while maintaining comprehensive information extraction through systematic analysis of all data entries.
3Adaptability or versatility
If manual analysis is used to focus on specific types of information, then users can evaluate particular trends, but bias is introduced in the analytical results
Solution Approach 1:
The patent segments the analysis process into distinct functional modules: data reading, parsing, pattern identification, and result generation. Each module performs a specific function with clearly defined rules, eliminating the subjective bias inherent in manual analysis. The segmented approach allows the system to comprehensively analyze all types of information in the data file rather than selectively focusing on predetermined trends, thereby ensuring objectivity and reliability.
Data Source
AI summary
The present invention relates to methods and systems that use natural language processing (NLP) to read data from a file and analyze the data based on user defined parameters. According to an illustrative embodiment of the present disclosure, a system can process and analyze a data file by finding trending themes across data entries. According to a further illustrative embodiment of the present disclosure, the system can search for reoccurring or repeated words/phrases based on Ngrams (i.e., n-grams). The system can be adapted to search for Ngrams of varying length depending on the information sought and can sort the results by Ngram length.