Spreadsheet Table Conversion Using Header Hierarchy
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Solution Overview
Problem
Existing spreadsheet tables pose challenges for automated transformation into relational tables due to their complex structures, making manual conversion tedious and time-consuming, and lacking effective automation techniques for understanding and processing by machines.
Innovation Solution
A method for automated spreadsheet table transformation involves detecting header areas and determining their hierarchical structures through cell merging, indent levels, and function relationships, enabling conversion to relational tables with a unified structure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If spreadsheet tables use flexible structures with complex headings and varying cell sizes for human interpretation, then ease of operation is improved, but device complexity increases making automated transformation difficult
Solution Approach 1:
The patent introduces an intermediary processing system that includes: (1) a table structure analysis module that detects header areas and determines hierarchical structures through cell merging and indent analysis, (2) a transformation module that converts the flexible spreadsheet structure into a standardized relational table format. This intermediary system bridges the gap between human-friendly flexible tables and machine-friendly structured data, resolving the contradiction by adding intelligence to handle the complexity rather than simplifying the original structure.
2Manufacturing precision
If manual conversion of spreadsheet tables to relational tables is performed, then manufacturing precision is maintained, but productivity decreases due to tedious and time-consuming processes
Solution Approach 1:
The patent implements a self-service automated transformation system where the spreadsheet table itself provides the necessary structural information through its inherent features (cell merging, indents, header arrangements). The system automatically: (1) detects header areas and their hierarchical relationships, (2) identifies column relationships through function analysis, (3) generates the relational table structure without human intervention. This eliminates manual conversion while maintaining precision through algorithmic analysis of the table's own structural cues.
3Productivity
If automated transformation techniques are developed to improve productivity, then device complexity increases due to lack of effective automation methods for understanding complex table structures
Solution Approach 1:
The patent applies preliminary action by having the system pre-analyze and understand the spreadsheet table structure before transformation. The table structure analysis module performs preliminary detection of: (1) header area boundaries, (2) hierarchical relationships through cell merging patterns, (3) column relationships through function analysis. This preliminary understanding is stored as structured information that guides the subsequent transformation process, enabling automated productivity improvement without requiring overly complex real-time processing during conversion.
Data Source
AI summary
Implementations of the present disclosure provide a solution for spreadsheet table transformation. In this solution, one or more header areas and a data area of a spreadsheet table are detected. A hierarchical structure of each of the header areas is determined by analysis of cell merging and/or indents in the header area, and/or a function relationship between data items in corresponding cells of the data area. The spreadsheet table can be transformed to a relational table based on recognition of the hierarchical structure of the header area. In this way, by facilitating understanding of header structures based on the header hierarchy, it is possible to achieve automated transformation from spreadsheet tables to relational tables.