Unstructured Data Predictive Analysis System
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Solution Overview
Problem
Conventional predictive analysis methods are limited by their inability to effectively utilize unstructured data sources such as video, images, and narrative text, which are common in social media and multimedia platforms, due to the lack of structured formats associating variable entities with values and timestamps.
Innovation Solution
A method and system that generate instances from unstructured data sources, associate variable entities with influencers or performance indicators, and determine their values using detectors, allowing for the creation of predictive models that link influencers with performance indicators, thereby enabling predictive analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional preprocessing tools are used for structured data, then predictive analysis can be performed effectively, but unstructured data from social media and multimedia sources cannot be utilized
Solution Approach 1:
The patent introduces an intermediary processing layer that converts unstructured data into structured instances with variables, values, and timestamps. This intermediary transformation enables unstructured data from social media and multimedia sources to be compatible with conventional predictive analysis tools without requiring fundamental changes to those tools.
Solution Approach 2:
The system changes the parameters of unstructured data by extracting and organizing specific attributes (variables, values, timestamps) into a standardized structured format. This parameter transformation allows diverse unstructured data sources to be processed using existing predictive analysis methodologies designed for structured data.
2Quantity of substance
If unstructured data is used directly in predictive analysis, then data availability increases, but the lack of structured format prevents effective analysis
Solution Approach 1:
The patent extracts key elements (variables, values, timestamps) from unstructured data sources and separates them into structured components. This extraction process makes the data accessible to predictive analysis tools while preserving the original unstructured data sources, thereby increasing both data availability and ease of operation.
Solution Approach 2:
The system segments unstructured data into discrete structured instances with defined variables, values, and timestamps. This segmentation transforms continuous unstructured data streams into analyzable discrete units that can be easily processed by conventional predictive analysis systems.
3Measurement precision
If conventional predictive analysis methods are applied, then analysis accuracy is maintained, but the scope of analyzable data sources is limited
Solution Approach 1:
The patent creates a universal data transformation framework that can handle multiple types of unstructured data sources (social media, video, images, audio) and convert them into a common structured format. This multi-functional approach maintains analysis accuracy across diverse data sources while expanding the scope of analyzable data beyond traditional structured sources.
Data Source
AI summary
A method of performing predictive analysis includes generating, using a computational device, an instance from an unstructured data source. The method further includes associating a variable entity with the instance. The variable entity is associated with an influencer of a set of influencers or a performance indicator of a set of performance indicators. In another example, the method includes determining, using the computational device, a value of the variable entity from the instance based on a value-detection rule and generating, using the computational device, a model associating the set of influencers with the set of performance indicators using the value of the variable entity.