Entity Reference Construction for Master Data Management
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Solution Overview
Problem
Current master data management (MDM) systems are unable to effectively integrate information from unstructured data sources, such as news reports and emails, due to incomplete and imprecise textual references, which hinders the accuracy of entity resolution and relationship discovery.
Innovation Solution
A system that utilizes a processor to analyze unstructured data, extract attribute values, and construct entity references, linking them to corresponding entities in the MDM system, thereby enhancing structured information with supplemental data from unstructured sources, while accommodating noisy and incomplete text.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If MDM systems integrate information from unstructured data sources, then the comprehensiveness of entity information is improved, but the accuracy and trustworthiness of entity resolution deteriorates due to incomplete and imprecise textual references
Solution Approach 1:
The patent introduces an intermediary entity reference construction process that bridges unstructured text and structured MDM data. The system extracts attributes from unstructured text, constructs entity references as intermediate representations, and then matches these references to existing MDM entities. This intermediary approach allows the system to leverage unstructured data while maintaining the accuracy standards of structured data through the matching and verification process.
Solution Approach 2:
The system changes the parameters of entity representation by extracting multiple attributes from unstructured text and storing them as structured entity references in the MDM system. This transformation allows the system to accommodate noisy and incomplete text by representing entity information in a standardized format with defined attributes, enabling subsequent accurate matching and resolution.
2Adaptability or versatility
If MDM systems process unstructured data with noisy text and spelling variations, then the versatility of data sources is improved, but the difficulty of detecting and measuring entity attributes increases
Solution Approach 1:
The system performs preliminary action by pre-defining entity models with specific attributes and data types before processing unstructured data. This allows the extraction process to focus on identifying and populating predefined attributes, making the system more adaptable to different unstructured data sources while maintaining consistent attribute detection through the established entity model framework.
Solution Approach 2:
The patent implements a universal entity reference construction process that can handle multiple types of unstructured data sources (text files, emails, chat logs, etc.) through a common extraction and matching mechanism. The system uses generic attribute extraction and entity matching algorithms that work across different data formats and sources, enhancing versatility while managing the complexity of noisy text through standardized processing.
3Productivity
If MDM systems extract and link entity references from unstructured data, then the productivity of information integration is improved, but the device complexity increases due to additional processing requirements
Solution Approach 1:
The system segments the complex task of integrating unstructured data into distinct modules: attribute extraction from text, entity reference construction, entity matching, and data linking. This segmentation allows each component to be optimized independently and processed in a streamlined sequence, improving overall productivity while managing system complexity through modular architecture.
Data Source
AI summary
According to a present invention embodiment, a system supplements structured information within a data system for entities based on unstructured data. The system analyzes a document with unstructured data and extracts attribute values from the unstructured data for one or more entities of the data system. Entity records with structured information are retrieved from the data system based on the extracted attribute values. Entity references for corresponding entities of the data system are constructed based on a comparison of the retrieved entity records and the extracted attribute values. The entity references are linked to the corresponding entities within the data system, wherein the entity references include extracted attributes from the unstructured data for corresponding linked entities. Embodiments of the present invention further include a method and computer program product for supplementing structured information within a data system for entities based on unstructured data in substantially the same manner described above.