Hierarchical Sub-list Indexing for Fast Database Retrieval
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Solution Overview
Problem
Current navigation systems face challenges in managing large databases of geographic data due to limited computer resources, leading to slow data access and processing delays, especially when using speech recognition or tactile input systems.
Innovation Solution
A vehicle navigation system that indexes data sub-lists separately using unique prefixes or initial characters, allowing for faster retrieval of data sub-list elements without requiring extensive memory or computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional database indexing methods are used to manage large geographic data lists, then data access speed is improved, but memory consumption and computational load increase significantly
Solution Approach 1:
The patent divides the large geographic data list into multiple sub-lists based on hierarchical categories (e.g., countries, states, cities). Each sub-list is indexed separately with its own index structure, allowing the system to manage and access data in smaller, more memory-efficient units rather than loading a single comprehensive index into memory.
Solution Approach 2:
The patent introduces a hierarchical dimension to the indexing structure by organizing data into multiple levels (country → state → city). This multi-dimensional approach allows the system to navigate through categories rather than searching through all data simultaneously, reducing the memory footprint of individual index structures while maintaining fast access paths.
2Productivity
If comprehensive indices covering all data entries are created, then search efficiency is improved, but device complexity and resource requirements increase
Solution Approach 1:
The indexing structure is segmented into multiple hierarchical levels, with each level managing a specific category of geographic data. Instead of one complex index covering all data, the system uses several simpler indices organized in a hierarchy, reducing the complexity of individual index structures while maintaining overall search efficiency.
Solution Approach 2:
The system pre-organizes data into hierarchical categories and creates indices for each category before search operations occur. This preliminary organization allows the search function to quickly navigate through predefined categories rather than processing unstructured data, improving search efficiency without requiring complex runtime processing.
3Quantity of substance
If virtual memory and memory swapping techniques are used to handle large indices, then data storage capacity is improved, but processing delays increase
Solution Approach 1:
By segmenting the index into hierarchical sub-lists, the system keeps only the necessary portions of each index in memory during runtime. Each hierarchical level maintains a manageable subset of data that can fit in available memory, eliminating the need for virtual memory and memory swapping while avoiding processing delays.
Data Source
AI summary
A vehicle navigation system having an input device, a storage device, a processor, and an output device. The storage device stores a database of geographical locations, such as the names of states, cities, streets, or countries. The database has a data list that includes data sub-lists, where the data sub-lists may have one or more data sub-list elements. Each data sub-list may have an assigned unique name. The data sub-lists also may be divided into parts, such that each part is assigned a unique name. The processor is operative to index the data sub-lists or the parts of a divided data sub-list. The processor may be further operative to search the database for a data sub-list element given an input from a user, and the output device may output one or more data sub-list elements from the database based on the search performed by the processor.