Master Data Matching Using Behavioral Transaction Patterns

The patent transitions from one-dimensional physical address matching to multi-dimensional behavioral data matching. Instead of relying solely on location-based attributes, the system incorporates transactional patterns, purchasing behaviors, and temporal data across multiple dimensions to identify duplicate master data records, thereby maintaining accuracy in virtual environments where physical addresses are insufficient.

The patent changes the matching parameters from static physical address fields to dynamic behavioral parameters including transaction frequencies, purchase patterns, and temporal characteristics. This parameter transformation enables the system to adapt to virtual environments where traditional location-based identifiers lose their discriminative power.

The patent segments the complex matching process into distinct modules: data collection from multiple sources, behavioral pattern extraction, similarity scoring, and decision-making. This segmentation allows each component to handle specific aspects of the matching task independently, reducing overall system complexity while maintaining high accuracy through coordinated operation of specialized sub-systems.

The patent introduces behavioral pattern analysis as an intermediary layer between raw transactional data and matching decisions. This intermediary processes and transforms complex behavioral data into meaningful similarity scores, simplifying the final matching decision process while preserving the accuracy benefits of comprehensive behavioral analysis.