Spreadsheet Table Analysis via Semantic Input Detection
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Solution Overview
Problem
Existing data analysis tools require users to have specific skills and knowledge of formulas, making complex data analysis in data tables difficult and unintuitive, especially for users who do not utilize the grid interface effectively.
Innovation Solution
A solution that determines analysis operations based on user inputs in a data table's semantics, allowing users to perform operations like data statistics, selection, and transformation directly within the grid interface, supporting natural language inputs and presenting results in related regions, thereby simplifying and enhancing user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional data analysis tools are used, then data analysis capability is provided, but user operation complexity increases and ease of operation deteriorates
Solution Approach 1:
The system performs data analysis automatically by detecting user inputs (such as cursor positioning, cell selection, or typing in formula bars) and executing appropriate analysis operations without requiring users to manually configure complex parameters or learn specialized languages. The system serves itself by autonomously determining analysis types, selecting data ranges, and presenting results in the grid interface.
Solution Approach 2:
The patent introduces an intermediary analysis system that sits between the user and the raw data table. This intermediary layer translates simple user inputs into complex analysis operations, acting as a mediator that converts user-friendly interactions into sophisticated data processing tasks while maintaining the familiar grid interface as the interaction medium.
2Adaptability or versatility
If specialized analysis tools and formulas are provided, then data analysis functionality is enhanced, but learning curve and operation difficulty increase
Solution Approach 1:
The system automatically determines what analysis operations to perform based on detected user inputs and data table semantics, eliminating the need for users to learn specialized analysis languages or formulas. The system serves itself by autonomously selecting appropriate analysis methods, configuring parameters, and executing operations while presenting results directly in the grid interface.
Solution Approach 2:
The patent creates a universal analysis system that can perform multiple types of data analysis operations (statistical analysis, trend detection, data transformation, etc.) through a single unified interface. The system adapts to different user inputs and automatically selects from various analysis functions, providing multi-functionality without requiring users to learn multiple specialized tools or syntaxes.
3Adaptability or versatility
If complex analysis operations are enabled, then analytical capability is improved, but user skill requirements increase
Solution Approach 1:
The system performs complex analysis operations autonomously by detecting user inputs and automatically determining appropriate analysis methods, data ranges, and parameters. The system does not rely on user expertise to configure or execute analysis operations, as it self-determines the analysis workflow and presents results directly in the grid interface, thereby eliminating skill dependency while maintaining high analytical capability.
Solution Approach 2:
The patent performs preliminary analysis of user inputs and data table semantics before executing analysis operations. The system pre-processes user inputs to understand intent, pre-configures analysis parameters based on detected contexts, and pre-prepares data ranges, thereby enabling complex analysis operations to be executed reliably without requiring users to have specialized knowledge or perform complex setup procedures.
4Ease of operation
If natural language processing is implemented, then ease of operation improves, but system complexity increases
Solution Approach 1:
The patent introduces a natural language processing intermediary layer that translates user inputs (such as text in formula bars or voice commands) into structured analysis operations. This intermediary layer handles the complexity of language interpretation, semantic analysis, and operation mapping, while presenting a simple interface to users and maintaining compatibility with the existing grid interface paradigm.
Data Source
AI summary
According to implementations of the present disclosure, there is proposed a solution for analyzing a data table in response to a user input. In this solution, a user input in a cell of a data table is determined. The data table comprises a plurality of cells arranged in rows and columns. An analysis operation for the data table is determined based on semantics of the data table and the user input, the analysis operation corresponding to the user input. Further, a result of the analysis operation is presented in a region of the data table related to the cell. In this way, grid characteristics of the data table can be utilized to provide the result of the analysis operation as desired by a user and simple, efficient and user-friendly data analysis can be facilitated.