Progressive Fuzzy Search Relaxation for Database Precision
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Solution Overview
Problem
Existing database search methods are inefficient in handling large datasets with multiple text fields, as they do not account for spelling errors and require manual verification, especially in batch mode searches, and do not consider different combinations of search terms effectively.
Innovation Solution
A computer-implemented method and system that performs fuzzy searches by progressively relaxing search terms, modifying data to account for spelling, typographical, and phonological errors, and ranking matches based on accuracy, eliminating the need for manual verification by using a multicolumn database table with predefined data types like name, street address, city, state, and zip.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If exact matching search is performed on all fields, then search precision is improved, but search time increases and spelling errors cannot be handled
Solution Approach 1:
The patent segments the search process into multiple iterations with progressively relaxed constraints. Each iteration searches with different combinations of fields and constraint levels, allowing the system to balance precision and time by stopping when sufficient results are found without requiring exhaustive exact matching of all fields
Solution Approach 2:
The patent changes search parameters dynamically by modifying constraint strictness across iterations. It transitions from exact matching to fuzzy matching, and from searching all fields to searching subsets of fields, thereby adjusting the balance between search precision and execution time based on results obtained
2Reliability
If all field combinations are searched for exact matches, then completeness of results is improved, but manual verification burden increases
Solution Approach 1:
The patent implements self-service by automatically performing fuzzy matching and ranking operations that would otherwise require manual verification. The system autonomously handles spelling error correction, phonetic matching, and result ranking, eliminating the need for users to manually verify each result while maintaining completeness through multiple search iterations
3Ease of operation
If fuzzy matching is applied to handle spelling errors, then ease of searching is improved, but search precision decreases
Solution Approach 1:
The patent applies dynamic fuzzy matching where the degree of fuzziness adjusts across iterations. Early iterations use stricter matching with longer field combinations, while later iterations use more permissive fuzzy matching with fewer fields. This dynamic adjustment maintains precision when possible while enabling fuzzy searching when necessary, resolving the contradiction between ease of searching and search precision
Data Source
AI summary
Disclosed herein is a computer implemented method and system that progressively relaxes search terms provided by a user. Data of predefined types is stored in a database. The data is obtained by uniquely modifying data previously stored in the database, based on the predefined types. Search terms of predefined types are accepted from the user. The search terms are compared with the stored data to find exact matches, if length of the search terms exceeds a predefined value. On not finding exact matches, the accepted search terms are modified uniquely based on the predefined types to structure first alternative queries. The first alternative queries are compared with the stored data to find exact matches. On not finding exact matches, the first alternative queries are modified based on the predefined types to structure second alternative queries. The second alternative queries are compared with the stored data to find approximate matches.