Design and Implementation of a Data Reconciliation System Using Deterministic Fuzzy Matching with AI-Assisted Explainability and Confidence Analysis

Key Points

• The aim is to assess the effectiveness of a data reconciliation system in improving waste management knowledge.
• Implemented a deterministic fuzzy matching algorithm linked to an AI-driven explainability framework.
• Examined the impact of the system through education programs on waste management.
• Utilized confidence analysis to evaluate information reliability.
• Observed significant improvement in waste management knowledge among participants after training.
• Demonstrated increased effectiveness attributed to AI-assisted analysis.
• Identified areas for further optimization in data reconciliation.