Record Matching Using Unstructured Data Attributes
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Solution Overview
Problem
Current master data management systems face challenges in accurately matching and linking customer data from different sources due to the presence of unstructured information, which is not effectively utilized in record matching processes.
Innovation Solution
A method for record matching in a database system that processes unstructured data objects to identify attribute values, compares similarity levels between records, and determines entity representation by evaluating occurrence properties and contribution weights, enabling improved accuracy in matching records.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional structured data matching methods are used, then the matching process is simple and fast, but the accuracy is insufficient due to ignoring unstructured information
Solution Approach 1:
The patent segments unstructured data objects into discrete attribute values that can be extracted and compared individually. Each unstructured object is processed to identify specific attribute values, which are then used in the matching process alongside structured data attributes, thereby improving matching accuracy without overwhelming system complexity
Solution Approach 2:
The patent introduces an intermediary processing layer that extracts attribute values from unstructured data objects. This intermediary step transforms unstructured information into a format that can be systematically compared with structured data, enabling accurate matching while maintaining manageable process complexity through modular design
2Measurement precision
If unstructured data processing is implemented, then the record matching accuracy improves, but the processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary processing of unstructured data objects by pre-extracting and storing attribute values before the actual matching operation. This preliminary action prepares the data in advance, so that during matching, only comparison operations are needed, significantly reducing the time penalty associated with processing unstructured data
Solution Approach 2:
The patent selectively processes only the necessary attribute values from unstructured data objects that are relevant to the matching criteria, rather than processing all possible attributes. This partial action approach extracts only the essential information needed for accurate matching, reducing unnecessary computational overhead and processing time
Data Source
AI summary
A computer implemented method comprising processing the unstructured objects of each record of records of a database for identifying a set of one or more values of attributes in the unstructured objects of the each record. The sets of unstructured attribute values of two records of the database may be compared for determining a similarity level between the two sets. It may be determined whether the two records are representing a same entity based on the comparison result.