Automated Demographic Analysis via Frame-Based Search
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for determining demographics from search result bases are inefficient, as they often rely on manual processes and lack automated tools to quickly generate demographic data, hindering the productive use of research products.
Innovation Solution
The development of a method and apparatus for automated demographic data generation from search result bases using frame-based search engines, which analyze and organize search results to provide demographic insights through Confidence Distributions and frame extraction rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual processes are used to determine demographics from search result bases, then measurement precision may be maintained through human judgment, but productivity is significantly reduced due to time-consuming manual analysis
Solution Approach 1:
The patent replaces manual demographic analysis with an automated computer-based system that uses frame extraction rules and confidence distributions to determine demographic characteristics of search result bases, eliminating the need for manual processing while maintaining systematic analysis
Solution Approach 2:
The system enables self-service demographic analysis by automatically extracting frames from search results, applying extraction rules, calculating confidence distributions, and generating demographic data without requiring manual intervention, allowing the system to serve its own demographic determination needs
2Productivity
If automated tools are implemented for demographic data generation, then productivity is enhanced through faster processing, but device complexity increases due to the need for frame-based search engines and analysis algorithms
Solution Approach 1:
The patent segments the demographic analysis process into distinct components: frame extraction, rule application, confidence distribution calculation, and demographic determination. This modular segmentation manages complexity by breaking down the automated system into manageable, independent modules that can be developed and maintained separately
Solution Approach 2:
The frame-based search engine and extraction rules serve multiple functions: they identify demographic information, calculate confidence distributions, and generate demographic data across different search contexts. This multi-functionality reduces overall system complexity by using a single versatile framework rather than separate specialized tools
Data Source
AI summary
Techniques are presented for producing demographics, in an automated fashion, from a search result of computer-accessible content. While the demographics can be determined for a research product that has been produced by any technique, they are particularly useful when applied to an automated frame-based search approach. Frame-based search engines are presented for technology profiling, healthcare-related search and brand research. Determination of a demographic proceeds at two levels: member and population. At the member level, a demographic characteristic can be determined applicable with either total or partial certainty. Each value assigned by a demographic, to a population member, has a confidence level associated with it and the assignments can be represented by a Confidence Distribution. Summarization of a demographic, at the population level, depends upon whether the certainty assignments, at the member level, are total or partial. Declarant Demographics are presented. Approaches, to determining Declarant Demographics, are presented.