Document Management Learner for Automatic Folder Specification
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Solution Overview
Problem
Document management systems require users to manually set storage conditions for electronic documents, which is labor-intensive and time-consuming, especially for new documents, as users need to determine the appropriate folder based on document attributes without prior knowledge of the folder structure.
Innovation Solution
A document management apparatus that uses a learner, such as a deep neural network, to analyze the content and service attributes of electronic documents to automatically specify the storage destination folder for new documents, reducing the need for manual input by learning from existing document attributes and folder structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If a learner is used to automatically specify storage folders for electronic documents, then user effort and time are reduced, but the accuracy of folder specification may deteriorate without considering service attributes
Solution Approach 1:
The patent changes the input parameters of the learner from only document content to include both document content and service attributes. This allows the learner to accurately capture the relationship between service attributes and folder selection, improving specification accuracy while maintaining automation benefits
Solution Approach 2:
The system uses the learner to learn from historical data about service attributes and folder selections, continuously improving its accuracy. The learner processes feedback from past document storage decisions to refine its folder specification capability for new documents
2Measurement precision
If storage conditions are manually set for each electronic document, then folder specification accuracy is maintained, but user labor and time consumption increase significantly
Solution Approach 1:
The system enables self-service by using a learner to automatically specify storage folders based on document content and service attributes. This eliminates the need for manual user intervention in setting storage conditions, significantly improving productivity while maintaining accuracy through attribute-based learning
Solution Approach 2:
The learner acts as an intermediary between the document management service and the folder structure. It processes service attributes and document content to determine appropriate storage locations, bridging the gap between automatic processing and accurate folder specification
3Speed
If the learner only considers document content without service attributes, then processing speed is maintained, but the ability to accurately specify folders deteriorates
Solution Approach 1:
The learner is designed to process multiple types of input data simultaneously - both document content and service attributes. This multi-functional approach allows the system to maintain processing speed while improving accuracy by considering all relevant factors in folder specification
Data Source
AI summary
A document management apparatus provides an electronic document management service for managing electronic documents by storing the electronic documents in plural folders. The document management apparatus includes a processor configured to cause a learner to learn such that the learner specifies a folder in which an electronic document is stored, based on content of the electronic document stored in the folder and a service attribute assigned to the electronic document by the electronic document management service, and specify a storage destination folder in which a new electronic document is to be stored, based on content of the new electronic document and a service attribute of the new electronic document.