Level-Based Hierarchy Encoding with Sibling Links
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Solution Overview
Problem
Converting level-based data formats into annotated hierarchies is challenging, particularly due to difficulties in maintaining links between sibling nodes and computing hierarchies effectively.
Innovation Solution
A system and method that involves a central module interacting with a source module to encode level-based data tables, generating an encoded table with sibling node information, and then using a depth-first search to create an annotated hierarchy, facilitating efficient tree representation and navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If level-based data format is used to store hierarchical data, then data compression is improved and redundant information is reduced, but conversion to annotated hierarchy structure becomes difficult and complex
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing ancestor relationships and level information in the level-based table during data insertion. This preprocessing enables efficient hierarchy construction later without requiring complex real-time computations, resolving the contradiction between data compression and conversion complexity.
Solution Approach 2:
The patent introduces an intermediary encoding scheme that transforms level-based data into an annotated hierarchy format through intermediate representation. This intermediary structure facilitates the conversion process by bridging the gap between the compressed level-based format and the hierarchical structure, reducing conversion complexity while maintaining compression benefits.
2Loss of information
If each row in level-based table represents entire path from root to leaf node, then data completeness is improved, but column sizes increase and hierarchy depth is limited
Solution Approach 1:
The patent segments the hierarchical path information into discrete level columns, where each column represents a specific hierarchy level. This segmentation allows the data to be stored in a structured manner that maintains path completeness while managing column sizes through systematic organization of hierarchical levels.
Solution Approach 2:
The patent changes the parameter representation by using level-based encoding where each column corresponds to a hierarchy level rather than storing complete paths as single strings. This parameter transformation enables better data organization and reduces the effective length of stored information while preserving path completeness.
3Productivity
If annotated hierarchy structure is constructed from level-based data, then traversal efficiency is improved, but computation complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-establishing parent-child relationships and ancestor links during the hierarchy construction phase. This preprocessing creates the annotated structure that enables efficient traversal operations later, resolving the contradiction between traversal efficiency and computation complexity by shifting computational burden to the initial construction phase.
Data Source
AI summary
Disclosed herein are system, method, and computer program product embodiments for the translation of a level based format, where each record contains a complete individual path from the highest to the lowest leaf level, to an annotated hierarchy through a generator function which through mapping and encoding on a level-by-level basis, keeping track of sibling links, is able to perform a depth-first pre-ranking order assessment of original data, to produce an annotated hierarchy which may be utilized by a user.