Sound-Based Identifier Encoding for Database Query Efficiency
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Solution Overview
Problem
Databases face inefficiencies and incomplete query results due to inconsistencies in data organization and identification, particularly with text-based identifiers for vendors, leading to resource wastage and delays in machine learning model training.
Innovation Solution
The implementation of sound-based identifiers using the double metaphone algorithm for preprocessing and encoding text-based identifiers, which are then sorted and organized into hybrid prefix tree lists, allowing for efficient data retrieval and management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If text-based identifiers are used for vendor names in databases, then data can be stored and retrieved, but inconsistencies in data organization and identification result in inefficient query processing and incomplete query results
Solution Approach 1:
The patent transforms vendor names from text-based identifiers to sound-based identifiers by changing the parameter of identification from textual representation to phonetic representation. This is achieved through algorithms like Double Metaphone that convert text into sound codes, enabling consistent identification of vendors regardless of spelling variations or inconsistencies in the original text data.
2Loss of time
If traditional text-based vendor names are stored in databases, then vendor information can be managed, but computational resources are wasted and query time delays occur due to inconsistent data organization
Solution Approach 1:
The patent applies preliminary action by pre-processing vendor names into sound-based identifiers before they are stored in the database. Using algorithms like Double Metaphone, the system converts and normalizes vendor names in advance, creating a standardized phonetic representation that enables faster query processing later without requiring extensive computational resources during actual queries.
3Measurement precision
If vendor names with variations and inconsistencies are stored as text, then all vendor entries can be captured, but accurate identification of vendor names becomes difficult even when previously unknown
Solution Approach 1:
The patent introduces sound-based identifiers as an intermediary between the original text-based vendor names and the database storage system. This intermediary layer uses phonetic algorithms to translate various text representations of vendor names into consistent sound codes, enabling accurate identification and matching of vendors even when the original text varies or when vendors are previously unknown to the system.
Data Source
AI summary
Described herein are techniques, devices, and systems for database management using sound-based identifiers. The sound-based identifiers can be encoded based on text-based identifiers input into one or more databases. The sound-based identifiers can be preprocessed and encoded by encoding the text-based identifiers with a double metaphone algorithm. First sound-based identifiers can be sorted in a cluster associated with a node of a hybrid prefix tree list, based on a longest common prefix of the group. The first sound-based identifiers can be re-encoded as second sound-based identifiers and organized into sub-clusters associated with nodes, based on characters of the second sound-based identifiers positioned after characters associated with the clusters. The re-encoded sound-based identifiers can be determined based on metadata. A query can be received and utilized to identify a re-encoded sound-based identifier. Data associated with the re-encoded sound-based identifier can be transmitted based on the query.