Hierarchical Document Flow Determination for Memory Efficiency
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Solution Overview
Problem
Existing business applications face memory inefficiencies due to the storage of redundant relational data in document flow databases, which can be onerous in scenarios involving large numbers of documents.
Innovation Solution
A hierarchical data model is used to assign a tree-like structure to documents, focusing only on direct document-document relations, allowing for the assembly of a tabular representation of document flow without storing redundant data, and providing this representation as a virtual table to business applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If indirect or transitive relations are stored in the relational database to provide complete document flow information, then data completeness is improved, but memory requirements increase significantly
Solution Approach 1:
The system pre-calculates and stores aggregation levels (e.g., total document counts, summary statistics) for different hierarchy levels in advance. These pre-computed aggregations are stored efficiently without requiring storage of all individual transitive relations, thus providing complete flow information while reducing memory requirements.
Solution Approach 2:
The patent introduces a hierarchical abstraction layer between the raw document relations and the query interface. This hierarchy acts as an intermediary that pre-organizes documents into structured levels (individual documents → document groups → departmental groups → enterprise-wide groups), allowing complete flow information to be derived through hierarchical aggregation rather than storing all direct transitive relations.
2Measurement precision
If all transitive relations are calculated and stored to enable complete document flow analysis, then query accuracy is improved, but data processing time increases
Solution Approach 1:
The patent segments the document flow analysis into hierarchical levels (individual documents, document groups, departmental groups, enterprise-wide groups). Each level maintains precise relations appropriate to its scope, allowing accurate flow analysis to be performed at the required granularity without calculating all possible transitive relations across the entire dataset.
Solution Approach 2:
The system pre-calculates and stores aggregation data for each hierarchical level. When a query is executed, the system retrieves pre-computed aggregations rather than calculating transitive relations in real-time, thus maintaining measurement precision while significantly reducing data processing time.
3Ease of manufacture
If a flat relational database structure is used to store document relations, then ease of implementation is improved, but scalability deteriorates with large numbers of documents
Solution Approach 1:
The patent introduces a hierarchical dimension to the traditional flat relational structure. Documents are organized into multiple hierarchical levels with parent-child relationships, adding a structural dimension that enables efficient querying and analysis of large datasets while maintaining implementation simplicity through standard relational database techniques.
Solution Approach 2:
The hierarchical database structure serves multiple functions: it enables efficient storage of large document sets, provides scalable query capabilities across different granularities, supports various analysis perspectives (individual, group, departmental, enterprise-wide), and maintains implementation simplicity through standardized relational operations.
Data Source
AI summary
A computer-implemented method is used to determine a document flow of documents, data on the documents being stored in a documents database. The method involves assigning a hierarchical tree-like structure to the documents. The hierarchical tree-like structure includes one or more hierarchy levels beginning with a document assigned to a root node of the tree-like structure. Each hierarchy level is defined by the direct relations between the documents assigned to tree nodes in the hierarchy level. The method further includes assembling, for a pre-determined number of hierarchy levels, a tabular representation of the hierarchical tree-like structure assigned to the documents, and providing the tabular representation as the document flow.