Boolean Index Generation for Database Search Optimization

Solution Overview

Problem

Existing database search systems face inefficiencies in processing search queries due to the need to search through vast numbers of records, leading to high computational overhead and latency.

Innovation Solution

The implementation of an index-generation engine that automatically generates Boolean indexes based on prior inquiries and returned records, identifies frequent indexes, and selects the most frequent index to expedite database searches by reducing the search space.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If the database system searches through all records to respond to search queries, then search result accuracy is maintained, but computational overhead and latency increase

Engineering Contradiction:

Improvesearch result accuracyVSAvoidsearch processing speed

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system performs preliminary actions by automatically generating Boolean indexes from historical inquiry datasets before actual search queries are executed. These indexes pre-identify frequent search patterns and candidate record sets, so when a search query arrives, the system can directly apply the pre-computed index instead of scanning all records, thus maintaining accuracy while improving speed

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The Boolean index acts as an intermediary between the search query and the full database. Instead of directly querying all records, the system first applies the Boolean index to filter and identify a candidate subset of records. This intermediary structure enables efficient searching by reducing the search space while preserving the ability to find all relevant records

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If the database system searches through all records to ensure complete results, then search accuracy is maintained, but the time required for search operations increases

Engineering Contradiction:

Improvesearch result completenessVSAvoidsearch latency

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by automatically generating Boolean indexes from historical inquiry datasets before actual search queries are executed. These indexes pre-identify frequent search patterns and candidate record sets, so when a search query arrives, the system can directly apply the pre-computed index instead of scanning all records, thus maintaining accuracy while improving speed

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system utilizes feedback from historical inquiry datasets to automatically generate and refine Boolean indexes. By analyzing patterns from past searches and their returned records, the system continuously improves the quality of indexes, making them more effective at identifying relevant candidate sets while reducing search time

Inventive Principle:

Principle #23Feedback

3Reliability

If the database system processes large volumes of search queries through full database scans, then comprehensive search results are achieved, but computational resources are excessively consumed

Engineering Contradiction:

Improvesearch result comprehensivenessVSAvoidcomputational overhead

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system extracts the essential search patterns and candidate record information from historical inquiry datasets to create compact Boolean indexes. These indexes contain only the critical information needed to identify relevant records, separating the essential search logic from the full database. This extraction reduces computational overhead by eliminating the need to process irrelevant records during search operations

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system performs preliminary actions by automatically generating Boolean indexes from historical inquiry datasets before actual search queries are executed. These indexes pre-identify frequent search patterns and candidate record sets, so when a search query arrives, the system can directly apply the pre-computed index instead of scanning all records, thus maintaining accuracy while improving speed

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS12321387B2Automatically generating search indexes for expediting searching of a computerized database

Publication Date: 2025.06.03 EQUIFAX INC

AI summary

Search indexes can be automatically generated and used for expediting searching of a computerized database. For example, a system can access an inquiry dataset that includes relationships between prior inquiries and returned records from a database. The system can then generate a set of Boolean indexes based on the prior inquiries. The system can then identify frequent indexes that occur at least a threshold number of times in the set of Boolean indexes and that have estimated candidate sizes that are less than a threshold size. The system can then select the frequent index with the highest frequency from among the frequent indexes. The selected frequent index can be subsequently used to expedite searching of the database in response to receiving a search query associated with the frequent index from a client device.