Document Attribute Management via Predictive Date Extraction
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Solution Overview
Problem
Existing document management systems do not effectively provide a date indicating the possibility of a document's future necessity as attribute information, limiting their ability to manage and retrieve documents based on future relevance.
Innovation Solution
An information processing apparatus and program that specify a second date, which is a date after a first date associated with a document's processing or written date, and provide this second date as attribute information, using OCR technology to extract relevant information from documents and determine the date based on stored character string databases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing document management systems only store processing dates or written dates, then the system maintains simple attribute structure, but the system cannot identify documents by future relevance
Solution Approach 1:
The system performs preliminary analysis of document content to predict future necessity dates before the actual need arises. By extracting key information such as deadlines, delivery dates, and event dates from document text, the system proactively assigns attribute dates that indicate when the document will be needed, enabling forward-looking document management rather than merely recording past processing dates
Solution Approach 2:
The patent introduces an intermediary attribute (the predicted future necessity date) that bridges the gap between the document's current state and its future utility. This intermediary attribute serves as a mediator that connects the document content with retrieval requirements, allowing users to search and organize documents based on future needs rather than just historical processing dates
2Measurement precision
If the system extracts and analyzes document content to determine future necessity dates, then future relevance identification is improved, but processing complexity increases
Solution Approach 1:
The system extracts only the critical date-related information from document content, such as deadlines, delivery dates, and event dates, rather than analyzing the entire document. This selective extraction approach maintains high precision in determining future necessity dates while minimizing processing complexity by focusing only on relevant textual elements
Solution Approach 2:
The patent changes the parameter of date attribution from historical (processing date or written date) to predictive (future necessity date). By transforming the temporal parameter from past-oriented to future-oriented, the system achieves more accurate measurement of document relevance while using automated text extraction methods to manage processing complexity
Data Source
AI summary
An information processing apparatus includes: an attribute giving unit that specifies a second date, which is a date after a first date corresponding to a date, on which processing is performed with respect to a document, or a date written in the document, based on information written in the document, and that gives the second date as attribute information of the document.