Metalabel Range Search Structures for Spatial Query Matching
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Solution Overview
Problem
Existing methods for organizing and searching electronic data in data processing systems are inefficient, particularly in handling geographic and dimensional information, leading to suboptimal search results and file organization.
Innovation Solution
Implementing a method that structures electronic data using heterogeneous string structures with embedded n-dimensional range structures, utilizing user-defined metalabels and geometric search structures like K-D trees, and optimizing with neural networks to enhance search efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional keyword-based organization methods are used, then data can be organized by content, but search efficiency is poor when handling geographic and dimensional information
Solution Approach 1:
The patent segments the data organization system into two distinct components: heterogeneous string structures for content-based organization (metalabels) and n-dimensional range structures for geographic and dimensional information. This segmentation allows each structure to specialize in handling specific types of data, improving overall search efficiency without compromising organizational capability.
Solution Approach 2:
The patent introduces n-dimensional range structures that add spatial and dimensional dimensions to the traditional keyword-based organization. By embedding geographic coordinates, elevation, and other spatial attributes in a structured n-dimensional framework, the system enables efficient spatial queries alongside traditional text-based searches, resolving the contradiction between content organization and geographic information handling.
2Measurement precision
If complex search structures are implemented to improve search accuracy, then matching precision improves, but device complexity increases
Solution Approach 1:
The patent merges heterogeneous string structures and n-dimensional range structures into a unified data organization system where both structures coexist and work together. The heterogeneous string structure handles metalabels and content-based organization, while the embedded n-dimensional range structure handles geographic and dimensional attributes. This merging allows the system to maintain high search matching precision across multiple data types without requiring completely separate systems.
Solution Approach 2:
The patent creates a universal data structure that can handle multiple types of queries simultaneously - text-based searches, geographic spatial queries, dimensional range queries, and combinations thereof. The n-dimensional range structure serves multiple functions including storing coordinates, elevation, and other spatial attributes, reducing the need for separate specialized structures and thereby managing complexity while maintaining precision.
3Adaptability or versatility
If multiple data structures are used to organize different types of information, then organizational versatility improves, but energy consumption increases
Solution Approach 1:
The patent embeds n-dimensional range structures within the heterogeneous string structure, creating a nested organization where spatial and dimensional data are integrated into the content-based organization framework. This nesting allows the system to maintain organizational versatility for different data types while avoiding the overhead of completely separate data structures, thereby reducing energy consumption compared to maintaining multiple independent structures.
Data Source
AI summary
A method in a data processing system and apparatus for organizing electronic data, structured or unstructured, with associated metalabels, on a recordable medium of a data processing system. The data items are structured in a heterogeneous metalabel search structure. Searching the plurality of metalabel search structures can then be done with a heterogenous-range query including at least one term and one range query. The query can also be specified in a natural language which is converted to the specific heterogenous-range query. Also provided is a method for searching using geometric shapes that are mapped into range-string queries where the ranges are d-dimensional hyper-rectangles or cubes that cover the geometric shape. A method to aid the selection of the appropriate shape is provided as well as a method to cost-efficiently select the hyper-rectangles and cubes to cover the shape.