Automated Document Classification and Rule Routing
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Solution Overview
Problem
Electronic data processing in computer networks is inefficient, particularly with large numbers of documents, as users often struggle to determine the correct destination for scanned data, leading to cumbersome manual selection of processing rules.
Innovation Solution
The SmartFeedback application automates the processing of electronic data by using OCR to classify documents, determining corresponding processing rules, and performing specified actions, such as routing and storage, with user confirmation and management options for classifications and rules on multiple levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual selection of processing rules is used for each document, then users have control over document routing, but the process becomes cumbersome and inefficient for large numbers of documents
Solution Approach 1:
The system performs preliminary classification of documents using OCR technology to extract text and identify document types before routing decisions are needed. Processing rules are pre-configured for different document classifications, so when a document arrives, the system automatically matches it to the appropriate rule without requiring manual intervention. This preliminary automated classification eliminates the time-consuming manual rule selection process while maintaining control through pre-established routing logic.
2Productivity
If automated classification is implemented to reduce manual effort, then processing efficiency improves, but system complexity increases
Solution Approach 1:
The system introduces an intermediary layer consisting of OCR text extraction and classification engines that bridge the gap between raw document input and routing decisions. These intermediaries automatically analyze document content, extract relevant features, and classify documents into predefined categories, which then trigger appropriate processing rules. This intermediary classification layer automates the routing process and improves productivity while managing complexity through modular, rule-based architecture rather than requiring complex AI models.
3Adaptability or versatility
If processing rules are stored remotely in a data store, then system flexibility and manageability improve, but access time and network dependency increase
Solution Approach 1:
The system performs preliminary loading of processing rules from the remote data store into local memory of the document processing system before document routing operations begin. This allows the system to maintain flexible, centrally-managed rules in the data store for adaptability, while simultaneously having fast local access to frequently used rules during document processing. The rules are cached locally to reduce network dependency and improve access speed during high-volume document routing operations.
Data Source
AI summary
An approach is provided for managing processing rules used to process electronic data in computer networks. An application provides the capability for users to define and manage classifications for electronic data. The application also provides the capability for users to define and manage processing rules for each classification. This may include specifying, for each processing rule, a classification to which the processing rule corresponds, one or more conditions under which the processing rule is to be applied and optionally, not applied, a priority for the processing rule, and one or more actions to be performed. The priority may be used to determine which rule is to be applied when more than one rule corresponds to a classification. The application supports the definition and management of classifications and rules on a logical group-by-logical group basis.