Genealogical Record Clustering for Historical Network Discovery
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Solution Overview
Problem
Existing genealogical research services and social networking platforms fail to provide insights into historical communities and relationships of ancestors, limiting the understanding of how ancestors were influenced by or participated in communities such as military units, religious congregations, neighborhoods, or professional organizations, and how they interacted with other members.
Innovation Solution
A computer-implemented method that normalizes genealogical records, stitches them into clusters corresponding to individuals, identifies life-event records indicating non-familial relationships, and generates a graphical user interface to display a historical network, utilizing Elasticsearch and graph databases like Amazon Neptune to represent these relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If genealogical records are normalized and stitched into clusters to identify historical relationships, then the understanding of ancestors' community involvement is improved, but the system complexity and data processing requirements increase
Solution Approach 1:
The patent segments the large-scale genealogical database into normalized individual records, then clusters them into manageable groups representing specific individuals. This segmentation allows the system to process and analyze historical relationships in discrete, organized units rather than as an overwhelming monolithic dataset.
Solution Approach 2:
The patent introduces life-event records as intermediary entities that connect multiple individual clusters. These life-event records serve as mediators that capture community-level interactions and events, enabling the system to infer historical relationships without requiring direct pairwise connections between all individuals.
2Loss of information
If life-event records are analyzed to identify non-familial relationships, then the contextual understanding of historical communities is improved, but the data processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary normalization of genealogical records into standardized formats before clustering and analysis. This preliminary action organizes the data in advance, making subsequent processing of life-event records and identification of non-familial relationships more efficient and reducing overall computational time.
Solution Approach 2:
The patent focuses analysis on specific life-event records that are most relevant to identifying non-familial relationships and community involvement, rather than processing every possible record. This selective approach captures sufficient historical context while avoiding unnecessary computational overhead.
3Ease of operation
If graphical user interface is generated to display historical networks, then the usability and accessibility of historical data is improved, but the system complexity increases
Solution Approach 1:
The patent creates a graphical copy or representation of the complex historical network data in the user interface. Instead of requiring users to interact with raw data structures or complex queries, the system generates visual representations that mirror the underlying relationships, making historical data accessible and understandable without exposing system complexity.
Data Source
AI summary
A computing server may receive genealogical records that include historical records of deceased individuals. The computing server may normalize the genealogical records into normalized genealogical records. Normalizing the genealogical records may include converting a text string of a genealogical record into a standardized format. The computing server may stitch the normalized genealogical records into a plurality of clusters. Each cluster corresponds to an individual and includes one or more genealogical records associated with the individual. The computing server may identify a life-event record that is commonly associated with a subset of clusters, the life-event record indicating that a plurality of deceased individuals are connected through a non-familial relationship in a life event documented by the life-event record. The computing server may cause a graphical user interface to display a representation of a historical network among the plurality of deceased individuals that are connected through the non-familial relationship.