Variable Name Vector Analysis for Dynamic Tabular Data
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Solution Overview
Problem
Existing tabular data analysis techniques struggle to analyze data with changed, added, or reduced variable names, as they require relearning or extraction of common columns, leading to inefficiencies and loss of information.
Innovation Solution
An information processing apparatus that acquires data with variable names and values, generates variable name vectors and value vectors, and combines them based on their correspondence relationship, enabling analysis even when variable names change, are added, or removed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If tabular data analysis technique is used with fixed column configuration, then analysis accuracy is maintained, but adaptability to data changes deteriorates
Solution Approach 1:
The patent changes the parameter representation from fixed column indices to variable name-based identification. By using variable names as keys to access data values, the system can adapt to changes in column configuration without affecting analysis accuracy, as the variable names themselves carry the semantic information needed for accurate analysis.
Solution Approach 2:
The patent introduces variable names as an intermediary between the data storage structure and the analysis process. Instead of directly referencing columns by position, the system uses variable names as mediators to access and identify data, enabling flexible adaptation to different data configurations while maintaining consistent analysis semantics.
2Reliability
If relearning is performed after column configuration changes, then analysis accuracy is maintained, but processing time and computational cost increase
Solution Approach 1:
The patent performs preliminary action by establishing variable name to data mapping during the initial data loading phase. This preliminary mapping allows the system to immediately handle data with different column configurations without requiring relearning, as the variable names are already prepared as identification keys for subsequent analysis operations.
3Adaptability or versatility
If only common columns are extracted for analysis, then compatibility between different data versions is improved, but information loss increases
Solution Approach 1:
The patent achieves universality by designing a system where variable names serve as universal identifiers that can map to different data configurations. The same variable name-based approach works across different data versions and configurations, allowing the system to handle diverse data structures without losing information, as all variables can be processed through the unified variable name mapping mechanism.
Data Source
AI summary
According to one embodiment, an information processing apparatus includes processing circuitry. The processing circuitry is configured to acquire data including a variable name and a value associated with the variable name, and a correspondence relationship between the variable name and the value. The processing circuitry is configured to generate a variable name vector corresponding to each variable name and a value vector corresponding to the value associated with each variable name. The processing circuitry is configured to combine the variable name vector and the value vector based on the correspondence relationship.