Document Access Control via Token Alignment Scoring

The patent segments the credential string into multiple tokens (words or character groups) rather than processing it as a single continuous string. This segmentation allows the system to create multiple candidate alignments by different ways of grouping and matching tokens, thereby reducing the impact of individual character recognition errors while maintaining fast automated processing.

The patent implements a dynamic matching approach that generates multiple candidate alignments between search and reference tokens, then evaluates them using scoring functions. Instead of a static exact match, the system adapts by considering various possible alignments and selecting the best match based on computed scores, thereby reducing false negatives caused by scanning errors while maintaining precision.

By segmenting credentials into tokens and creating extended sets of candidate alignments through different grouping methods, the system handles spelling variants and format differences systematically. This segmentation approach manages complexity by breaking down the matching problem into smaller, more manageable token-level operations rather than dealing with entire variable-format strings at once.

The patent evaluates multiple candidate alignments beyond what a simple exact match would require, but not all possible combinations are fully processed. The system uses scoring functions to evaluate candidates and can stop when a sufficient match is found, performing partial evaluation that balances accuracy improvement with time constraints. This excessive action principle allows the system to consider more options than minimum required while avoiding exhaustive computation.