Statistical Records Classification System
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Solution Overview
Problem
Existing records management programs face challenges in achieving accuracy due to limited flexibility in category membership and record management rules, leading to variability in classification results between different personnel and tools, and difficulties in processing records classified into multiple categories with different management rules.
Innovation Solution
A records management system that classifies records into multiple categories based on statistical values, combining assessments from automated tools and human operators to determine likelihood and confidence levels, and applies corresponding management rules for retention, production, and storage, using a category map to represent classification and management decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional binary classification rules are used, then classification simplicity is maintained, but classification accuracy deteriorates due to inability to capture nuanced record-category relationships
Solution Approach 1:
The patent transforms binary classification (yes/no) into a multi-parameter statistical assessment system that evaluates multiple attributes simultaneously, allowing nuanced classification decisions based on weighted combinations of evidence rather than simple threshold rules
Solution Approach 2:
The patent introduces statistical values and confidence scores as intermediary elements between raw record data and final classification decisions, enabling a gradual transition from uncertain evidence to definitive classification outcomes
2Reliability
If multiple category management rules are applied, then comprehensive record management is achieved, but processing complexity increases due to conflicting retention requirements
Solution Approach 1:
The patent transforms discrete, conflicting retention rules into a continuous statistical framework where retention decisions are based on aggregated confidence scores across multiple categories, allowing smooth resolution of conflicts rather than abrupt rule selection
Solution Approach 2:
The patent merges multiple category assessments and their associated management rules into a unified statistical decision framework that evaluates all categories simultaneously and produces a single coherent retention decision
3Productivity
If automated classification tools are used, then processing efficiency is improved, but classification accuracy deteriorates due to lack of human judgment
Solution Approach 1:
The patent creates a universal classification framework that can accommodate both automated tool outputs and human operator assessments, treating them as complementary data sources that together enhance rather than compete for classification accuracy
Solution Approach 2:
The patent implements feedback mechanisms where human corrections and validations of automated classifications are fed back into the statistical model, continuously improving the system's accuracy while maintaining high processing throughput
Data Source
AI summary
Statistical methods and apparatus for records management are disclosed. An example method for records management disclosed herein comprises classifying a record into at least one of a plurality of categories based on a statistical value, and performing an operation with respect to the record according to a rule associated with the at least one of the plurality of categories, wherein the operation is performed based on the statistical value.