Document Character String Pattern Generation for Search Efficiency
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Solution Overview
Problem
Existing information processing systems face challenges in efficiently assigning and searching for document data due to the lack of a standardized pattern for character strings, leading to impaired convenience and difficulty in data retrieval when different users assign character strings arbitrarily.
Innovation Solution
An information processing apparatus that acquires a history of character strings and specifies patterns within this history to generate candidate character strings for new document data, aligning with the document's content and task order, thereby suggesting appropriate character strings to users while maintaining flexibility in assignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users assign character strings to document data arbitrarily without standardized patterns, then users have flexibility in assignment, but searching, extraction, and rearrangement of document data becomes inefficient
Solution Approach 1:
The system changes the parameter of character string structure by extracting patterns from historical assignment data and generating candidate character strings that follow these patterns. This allows the system to maintain flexibility (users can still choose from multiple pattern-based candidates) while improving search and extraction efficiency through standardized structures.
Solution Approach 2:
The system performs preliminary action by generating candidate character strings based on extracted patterns before the user actually assigns a character string to new document data. This preliminary pattern-based suggestion improves future search and extraction efficiency while preserving user flexibility in the final selection.
2Adaptability or versatility
If users assign character strings arbitrarily without standardized patterns, then users have freedom in assignment, but consistency across different user assignments deteriorates
Solution Approach 1:
The system changes the structural parameters of character strings by enforcing patterns derived from historical data. This ensures consistency in the composition of assigned character strings across different users while still allowing freedom in selecting among pattern-compliant candidates.
Solution Approach 2:
The system uses feedback from historical character string assignment data to extract patterns and generate candidate suggestions. This feedback mechanism ensures that future assignments maintain consistency with past assignments while preserving user freedom through multiple candidate options.
3Productivity
If the system generates candidate character strings based on patterns from history, then consistency and efficiency improve, but system complexity increases
Solution Approach 1:
The system performs self-service by automatically extracting patterns from its own historical character string assignment data and using these patterns to generate candidate suggestions for new assignments. This self-service approach improves efficiency without requiring external pattern definition, though it does increase internal system complexity.
4Measurement precision
If the system extracts patterns from historical character strings, then candidate generation accuracy improves, but processing time increases
Solution Approach 1:
The system performs preliminary action by extracting patterns from historical data in advance and storing them for future use. When generating candidates for new document data, the system applies these pre-extracted patterns rather than re-extracting them, thereby improving accuracy while reducing processing time for each new assignment.
Data Source
AI summary
An information processing apparatus includes: a processor configured to: acquire a history of character strings assigned to document data by a user; specify a pattern in the character strings assigned to the document data using the history of the character strings; and generate a candidate character string to be assigned to document data of interest according to a character string included in the document data of interest and the specified pattern.