Hierarchical Path Determination Using Parent and Path Mappings
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for determining hierarchical paths in structured data sets are computationally expensive and inefficient, especially for longer paths, and require significant storage space, as they often involve traversing the data structure or maintaining extensive path tables.
Innovation Solution
The implementation of a structured data coordinator that creates parent and path mappings, allowing for efficient determination of paths by mapping nodes to their parents and paths within the hierarchy, reducing the need for extensive path tables and improving computational efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional traversal methods are used to determine hierarchical paths, then path determination can be achieved, but computational cost and time increase significantly for longer paths
Solution Approach 1:
The system pre-computes and stores parent-child relationships and hierarchical paths in a path table during data loading or updates. When path determination is needed, the pre-stored path information is retrieved directly without traversing the entire hierarchy, significantly reducing computational time for path queries.
Solution Approach 2:
A path table is introduced as an intermediary data structure between the hierarchical data and the path determination query. This intermediary stores pre-computed path information, allowing efficient retrieval without direct traversal of the hierarchical data structure, thus resolving the time efficiency problem.
2Speed
If extensive path tables are maintained to store all possible paths, then path determination speed improves, but storage space requirements increase significantly
Solution Approach 1:
Instead of storing complete paths from root to leaf for every node, the system segments the path information by storing only the immediate parent-child relationships and building paths on-demand or with minimal lookup. This segmentation reduces the quantity of stored data while maintaining efficient path determination capability.
Solution Approach 2:
The system stores only the necessary path information (parent pointers and immediate children) rather than all possible complete paths. This partial storage approach provides sufficient path determination capability without the excessive storage cost of storing every possible hierarchical path combination.
3Measurement precision
If hierarchical data is traversed node by node to find paths, then accurate path information is obtained, but computational complexity increases
Solution Approach 1:
The system creates a simplified representation (copy) of the hierarchical path relationships in the path table, storing parent-child mappings and path segments. This copy allows accurate path information to be retrieved through simple table lookups rather than complex traversals, reducing computational complexity while maintaining measurement precision.
Data Source
AI summary
Methods, machines, and stored instructions are provided for determining hierarchical paths to nodes based on stored information about the nodes. A node analyzer analyzes a hierarchy to create mappings that represent the hierarchy. The mappings may include a “parent mapping” that maps selected-level nodes to parent nodes of the selected-level nodes, and a “path mapping” that maps a plurality of nodes other than the selected-level nodes to a plurality of paths, within the hierarchy, to the plurality of nodes. A path module then determines path(s) to specified node(s) at least in part by mapping the specified node(s) to particular parent node(s) of the specified node(s) using the parent mapping. The path module also maps the particular parent node(s) to particular path(s) using the path mapping. The information from the path and parent mappings may be assembled to form path(s) within the hierarchy to the specified node(s).