Interval-Based Fuzzy Database Search Using Hash Value Segmentation
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Solution Overview
Problem
Large databases experience performance issues due to growing size and complex search queries, leading to delays in data retrieval, especially when handling range values and conditional statements.
Innovation Solution
A computer-implemented method generates non-overlapping search hash values from search parameters, allowing for efficient database searches by matching these hash values against reference fields, thereby reducing processing time and improving search efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional database search methods are used, then search accuracy is maintained, but search time increases exponentially with database size
Solution Approach 1:
The patent divides the continuous value range into discrete hash value intervals. Each database entry is assigned a hash value based on its value field, creating segmented buckets that group entries by their hash value ranges. This segmentation transforms the linear search problem into a localized search within specific hash value buckets, dramatically reducing search time as database size grows.
Solution Approach 2:
The patent introduces hash values as an intermediary layer between the search query and the actual database entries. Instead of directly comparing search parameters with all database values, the system first computes hash values from both the search parameters and database entries, then performs the comparison on these compressed hash representations. This intermediary transformation enables efficient filtering before detailed entry examination.
2Measurement precision
If complex search queries with conditional statements are processed, then search accuracy is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary hashing of database entry values during data insertion or preprocessing, storing the hash values alongside or instead of the original values in hash value fields. When a search query arrives, the system immediately computes hash values from the search parameters and compares them against the pre-computed hash values in the database, avoiding the need to evaluate complex conditional statements against every entry during the search execution phase.
Solution Approach 2:
The patent transforms the search problem from operating on original value parameters to operating on hash value parameters. By changing the parameter representation from raw database values to their hash equivalents, the system enables efficient comparison operations that work independently of the original value complexity, allowing conditional statements to be evaluated on compact hash representations rather than full-value comparisons.
Data Source
AI summary
A fuzzy database search technique is described for searching a database. The technique first prepares a database by first generating a reference hash value for each database entry to represent a value stored in a field of the database entry. The technique then receives search request to search for database entries in the database that have a value stored in the field that is within a provided range. The technique converts the search request into one or more search hash values and matches the search hash values to the reference hash values of the database to rapidly identify database entries that are likely relevant to the search.