Web Decision Matrix for Interactive Data Analysis

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Solution Overview

Problem

Current data retrieval tools, such as web crawlers, are inadequate for extracting and processing factual and numeric data for decision-making purposes, particularly in allowing interactive hypothetical changes to the data.

Innovation Solution

A software tool utilizing an expressly programmed computer that uses a web search engine to find relevant websites, extracts and stores pertinent data, applies operators and calculators to determine outcomes, and constructs a decision matrix for interactive manipulation of data fields and outcomes, enabling users to test hypothetical scenarios without needing separate displays for data and results.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If web crawlers are used to extract data from websites, then data retrieval is automated, but the extracted data cannot be interactively manipulated for hypothetical scenario testing

Engineering Contradiction:

Improvedata extraction automationVSAvoidinteractive hypothetical analysis capability

Core Design Contradiction:

Extent of automationVSAdaptability or versatility

Solution Approach 1:

The system segments data into structured fields within a decision matrix, separating raw extracted data from processed analytical results. This segmentation allows individual data points to be independently manipulated while maintaining automated extraction capabilities, enabling hypothetical scenario testing without sacrificing automation efficiency.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The decision matrix acts as an intermediary layer between automated web data extraction and interactive analysis. It transforms unstructured crawled data into a structured format that supports both automated processing and manual manipulation, bridging the gap between automation and adaptability.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Loss of information

If multiple data sources are aggregated for comprehensive analysis, then data completeness improves, but data processing complexity increases

Engineering Contradiction:

Improvedata completenessVSAvoiddata processing complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The decision matrix provides a universal structure that handles multiple data sources through standardized fields and calculations. Each column represents a data source with consistent field structures, allowing comprehensive data aggregation without proportionally increasing processing complexity through template-based automated operations.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system automatically changes data parameters through configured calculations and relationships within the matrix. When data is added or modified, dependent parameters are automatically updated through predefined formulas, reducing manual processing complexity while maintaining comprehensive multi-source data integration.

Inventive Principle:

Principle #35Parameter changes

3Manufacturing precision

If data is extracted and stored in structured fields, then data organization improves, but flexibility for interactive manipulation decreases

Engineering Contradiction:

Improvedata organizationVSAvoidinteractive manipulation flexibility

Core Design Contradiction:

Manufacturing precisionVSAdaptability or versatility

Solution Approach 1:

The decision matrix implements dynamic cells that can be independently manipulated while maintaining structured organization. Users can modify individual field values, add new rows or columns, and reconfigure calculations without disrupting the overall data structure, combining organizational precision with interactive flexibility.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system uses template-based copying where standardized data structures are replicated across multiple sources and scenarios. This allows structured organization through templates while maintaining flexibility, as users can copy and adapt templates to create hypothetical scenarios without redefining the entire data structure.

Inventive Principle:

Principle #26Copying

4Ease of manufacture

If separate displays are used for data input and results, then functional separation is achieved, but user interaction efficiency decreases

Engineering Contradiction:

Improvefunctional separationVSAvoiduser interaction efficiency

Core Design Contradiction:

Ease of manufactureVSEase of operation

Solution Approach 1:

The decision matrix merges data input, processing, and results display into a single integrated interface. All operations occur within the same matrix structure, eliminating the need to switch between separate displays and improving user interaction efficiency while maintaining functional separation through contextual toolbars and automated processing.

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS8250056B2Web-based decision matrix display

Publication Date: 2012.08.21 DEARBORN JOHN S

AI summary

A tool, using an expressly programmed computer which is programmed with executable instructions, that utilizes data mined from web queries to populate a decision matrix for finding an outcome to a query. The decision matrix is a displayed spreadsheet having rows representing fields that are typical for the query. The web yields data that is extracted and stored in the fields for a plurality of such sites. Calculators or operator methods are used for displaying a desired outcome using the fields. The field data may be entered manually when not found on websites. Data may be changed from actual data to represent hypothetical situation or a data field may be deleted. Columnar data is operated upon to determine different outcomes for comparison.