Ranking Unstructured Data via Structured Insights
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Solution Overview
Problem
Existing methods for business risk inquiries rely heavily on structured data sources, which may not include all relevant information, and manual searches for unstructured data are inefficient and often miss relevant documents.
Innovation Solution
A system that leverages structured data to identify and rank documentation from unstructured data sources, by extracting relevant insights from structured data to search for and analyze unstructured data, and scoring documents based on their relevance and risk indicators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If manual searches for unstructured data are performed, then comprehensive data collection is achieved, but search efficiency and time consumption deteriorate
Solution Approach 1:
The system performs preliminary actions by first searching structured data sources to identify relevant business entities and their attributes before conducting unstructured data searches. This preliminary structured data retrieval establishes search criteria and context that guide subsequent unstructured data searches, making them more efficient and targeted rather than performing comprehensive manual searches from scratch.
Solution Approach 2:
The system uses structured data as an intermediary to bridge the gap between general search queries and specific unstructured data retrieval. The structured data about business entities serves as a mediator that translates high-level search requirements into specific search parameters for unstructured data sources, enabling automated efficient searching without manual intervention.
2Ease of operation
If structured data sources are used, then data organization and searchability are improved, but data completeness and relevance deteriorate
Solution Approach 1:
The system merges structured and unstructured data sources into a unified search and analysis framework. It combines the organizational benefits of structured data with the comprehensiveness of unstructured data by integrating both data types into a single processing pipeline that leverages the strengths of each while mitigating their individual weaknesses.
Solution Approach 2:
The system creates a universal data processing platform that handles both structured and unstructured data using the same core architecture. The search system is designed to be multi-functional, capable of querying structured databases and scraping unstructured web content through a unified interface, thereby eliminating the need for separate specialized systems.
3Productivity
If automated data extraction is implemented, then processing speed is improved, but data accuracy and relevance deteriorate
Solution Approach 1:
The system implements feedback mechanisms where extracted unstructured data is validated against structured data sources and manually reviewed when necessary. The process continuously refines search criteria based on the quality and relevance of extracted information, adjusting automated extraction parameters to improve accuracy while maintaining high processing speeds through iterative optimization.
Data Source
AI summary
A system, computer program product, and method are presented for leveraging structured data and unstructured data, and, more specifically, to ranking documentation from unstructured data sources through leveraging insights provided by the structured data to facilitate associated business risk inquiries. The method includes identifying, by researching subject business entities, one or more structured data sources that include relevant structured data directed to the subject business entities. The method also include extracting the relevant structured data directed toward the subject business entities and leveraging the relevant structured data to identify unstructured data sources. The method further includes identifying documents from the unstructured data sources that have relevant information, thereby identifying relevant unstructured data, and leveraging the relevant structured data to determine relationships with the relevant unstructured data. The method also includes scoring each relationship and ranking each document from the unstructured data sources as a function of the scoring.