Enterprise Data Re-matching via Fuzzy Logic Scoring
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Solution Overview
Problem
Conventional advertising data management systems face inefficiencies due to duplicate records and lack of effective tools for scoring and comparing data across enterprise environments, leading to time-consuming and inefficient management and reporting.
Innovation Solution
The implementation of an enterprise data management system that utilizes fuzzy logic and a communication module to match and consolidate disparate advertiser and agency records, assigning unique IDs and prioritizing records for efficient management and reporting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional distributed systems are used to manage advertising data, then local entities can independently create and manage records, but duplicate records and data inconsistency occur across the enterprise
Solution Approach 1:
The system implements a feedback mechanism where matching scores are calculated and returned to users, who can then review and confirm or correct matches. This closed-loop feedback ensures that duplicate records are accurately identified and consolidated, maintaining data consistency across the enterprise while preserving local management autonomy.
Solution Approach 2:
The patent introduces an intermediary matching system that acts as a mediator between distributed local systems and the central enterprise database. This intermediary calculates matching scores, identifies duplicates, and facilitates consolidation without eliminating local management capabilities, thus resolving the contradiction between local autonomy and enterprise-wide consistency.
2Reliability
If manual methods are used to identify and consolidate duplicate records, then data consistency can be maintained, but significant time and resources are consumed
Solution Approach 1:
The system implements self-service by automatically calculating matching scores using algorithms that compare advertiser and agency records across the enterprise. The system autonomously identifies potential duplicates and presents them to users for confirmation, eliminating the need for manual record-by-record analysis and significantly reducing the time required for data consolidation.
Solution Approach 2:
The patent replaces manual mechanical methods of duplicate identification with automated computational algorithms. The matching score calculation system uses computer-based algorithms to rapidly analyze and compare records, substituting human effort with automated processing while maintaining accuracy through user review of the generated matches.
3Measurement precision
If fuzzy logic is used to match records with slight variations, then duplicate detection accuracy improves, but system complexity increases
Solution Approach 1:
The system handles record variations by changing the parameters used for comparison. Instead of requiring exact string matches, the patent uses fuzzy logic to compare parameters like advertiser names and agency names, allowing for slight variations while maintaining high detection accuracy. This approach balances precision with manageable system complexity.
Data Source
AI summary
A system and method for managing media advertising enterprise data including a process for learning enterprise data matching. An EDM (Enterprise Data Management) application module can be configured to include a set of rules at an enterprise level to manage disparate and disconnected records associated with an entity. A number of unmatched and enterprise entities that matches with respect to an active entity can be returned based on a fuzzy logic associated with various matching options stored in an EDM database. A matching process can then be performed to accurately match similar records regardless of manual input, location, and format of the records in a distributed system. Each unmatched record can then be assigned with a parent enterprise entity. Such an optimization mechanism can interactively manage and report records at the enterprise level in a simple and efficient manner.