Master Entity Associative Data Network for Unified Search
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Solution Overview
Problem
Conventional data management systems and online databases face challenges in connecting and analyzing data entities across various sources, including structured and unstructured data, to derive meaningful insights and connections effectively.
Innovation Solution
A system and method for generating a master entity associative data network using a data processor, which converts data from multiple sources into a computable relationship format, extracts and stitches data entities based on associations and common identifiers, and indexes them for high-performance search and analysis, enabling users to interact with an integrated data network of all mapped master entity types and their associations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional data management systems are used to store and manage large amounts of data, then data can be stored and organized, but the complexity of the structure makes it difficult for users to search and find desired information
Solution Approach 1:
The patent introduces an intermediary layer between the user and the data structure. This intermediary provides a simplified interface that translates user search queries into complex database queries, allowing users to search using simple terms while the system handles the complexity of navigating through large volumes of structured data
Solution Approach 2:
The patent replaces traditional mechanical database search mechanisms with semantic search technology. Instead of requiring users to navigate through rigid database structures using complex query languages, the system uses semantic understanding to interpret search terms and automatically retrieve relevant information, substituting the mechanical search process with an intelligent semantic matching process
2Reliability
If data from multiple sources is integrated to provide comprehensive information, then data completeness improves, but the complexity of integrating and managing diverse data formats increases
Solution Approach 1:
The patent implements a universal data integration framework that can handle multiple data formats and sources through a single unified system. The system provides multi-functional capabilities to ingest, parse, and integrate various data types (structured, semi-structured, unstructured) from different sources using common processing mechanisms, eliminating the need for separate integration solutions for each data type
Solution Approach 2:
The patent applies parameter changes by transforming diverse data formats into a standardized internal representation. The system changes the parameters of incoming data (format, structure, encoding) to match a unified schema, allowing comprehensive integration of multiple data sources while maintaining manageable complexity through standardization
3Adaptability or versatility
If semantic technology is used to describe data in machine-processable form, then data standardization improves, but the complexity of building and maintaining ontologies increases
Solution Approach 1:
The patent applies preliminary action by pre-building and pre-maintaining semantic ontologies and vocabularies before data integration is needed. The system establishes standardized semantic frameworks in advance that can be reused for multiple data integration tasks, avoiding the need to create and maintain complex ontologies for each individual integration requirement
Data Source
AI summary
A method and system for generating and using a master entity associative data network. The master entity associative data network system includes data sources storing data entities. Each data entity is of a specific entity type having specific entity properties, associations to other data entities, and an assigned common identifier label. Also, the master entity associative data network system includes a data processor configured to extract data entities from the data sources and extract associations to other data entities. The data processor stitches the data entities to each other based on at least one or more of the extracted associations, specific entity properties, and the common identifier label to generate one or more master data entities.