Automated Supplemental Content Generation via Keyword Popularity

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Generating supplemental content for media, such as quizzes or polls, can be costly and time-consuming, and not all media content has associated supplemental content, leading to viewer disappointment and potential loss of engagement.

Innovation Solution

A method and system that use a hardware processor to identify programs based on media data, extract keywords, determine popularity scores, and generate supplemental content such as quizzes or polls, which are then presented to users upon request, utilizing techniques like audio fingerprinting, image recognition, and popularity analysis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual content creation is used to generate supplemental content, then content quality and relevance are improved, but cost and time consumption increase

Engineering Contradiction:

Improvecontent qualityVSAvoidtime consumption

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system enables automatic generation of supplemental content by analyzing media content itself to extract keywords, determine popularity scores, and generate quizzes or polls without requiring manual human intervention for each content item

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system transforms the content generation process by changing from manual creation to automated generation based on extracted parameters such as keyword popularity scores, media type analysis, and content characteristics

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If manual content creation is used to generate supplemental content, then content relevance is improved, but production cost increases

Engineering Contradiction:

Improvecontent relevanceVSAvoidproduction cost

Core Design Contradiction:

Measurement precisionVSEase of manufacture

Solution Approach 1:

The system automatically generates supplemental content by analyzing the media content itself, extracting relevant keywords and determining popularity scores without requiring human creators for each item, thereby reducing production costs while maintaining relevance

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system replaces the mechanical process of manual content creation with an automated computational system that uses algorithms to analyze media content, extract keywords, and generate supplemental content based on popularity scores

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Reliability

If supplemental content is created for all media programs, then viewer engagement is improved, but resource requirements increase

Engineering Contradiction:

Improveviewer engagementVSAvoidresource requirements

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The system applies different levels of supplemental content generation based on local characteristics of each media program, such as popularity score, content type, and engagement potential, rather than uniformly generating content for all programs

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system generates supplemental content selectively for programs that meet certain criteria or have higher engagement potential, rather than creating content for all media programs, thereby optimizing resource usage

Inventive Principle:

Principle #16Partial or excessive action

4Productivity

If automated content generation is implemented, then productivity is improved, but content quality may deteriorate

Engineering Contradiction:

Improvecontent generation efficiencyVSAvoidcontent quality

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system replaces manual content creation with automated algorithms that analyze media content, extract keywords, and generate supplemental content based on popularity scores, achieving high productivity while maintaining quality through data-driven approaches

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS9161066B1Methods, systems, and media for generating and presenting supplemental content based on contextual information

Publication Date: 2015.10.13 GOOGLE LLC

AI summary

Methods, systems, and media for generating and presenting supplemental content based on contextual information are provided. In some implementations, a method for presenting content to a user is provided, the method comprising: identifying a program based on first media data; identifying one or more keywords associated with the program; determining a popularity score associated with each of the one or more keywords; obtaining one or more properties associated with a particular keyword of the one or more keywords based on the popularity score associated with each keyword; generating supplemental content for the program based on the one or more properties; receiving a request for supplemental content and second media data from a computing device; and upon determining that the second media data corresponds to the program, causing the generated supplemental content to be presented by the computing device.