Real-Time Entity Visualization for Knowledge Construction

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Solution Overview

Problem

Users face challenges in recalling characters and entities from long materials, such as books, due to multitasking and information overload while consuming content on electronic devices, leading to incomplete knowledge construction.

Innovation Solution

A computer-implemented method and system that detects user behavior and generates visualizations of entities and relationships in real-time by analyzing content, assigning weights based on relevance, and updating them dynamically, using a graphical user interface to display knowledge construction over time, incorporating external data from websites and social media.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Speed

If a user consumes long material content via electronic devices, then information consumption speed increases, but recall ability of characters and entities deteriorates

Engineering Contradiction:

Improveinformation consumption speedVSAvoidrecall ability of characters and entities

Core Design Contradiction:

SpeedVSLoss of information

Solution Approach 1:

The system extracts and stores entity information and relationships in advance during the content consumption process, building a knowledge representation structure before the user needs to recall. This preliminary extraction and organization of information allows users to quickly access previously consumed content without having to remember details, resolving the contradiction between fast consumption and poor recall.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary knowledge representation system that mediates between the consumed content and the user's memory. This intermediary structure stores entities, relationships, and contextual information, allowing users to access detailed information about characters and entities without needing to retain them in biological memory, thus enabling fast consumption while maintaining recall capability through the intermediary system.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If a user engages in multitasking while consuming content, then productivity increases, but knowledge construction completeness deteriorates

Engineering Contradiction:

Improvemultitasking efficiencyVSAvoidknowledge construction completeness

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The system automatically extracts entities, relationships, and contextual information from the consumed content without requiring active user engagement or attention. This self-service mechanism continuously builds the knowledge representation structure in the background, allowing users to multitask while the system independently captures and organizes information, thus maintaining knowledge construction completeness despite reduced user attention.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The knowledge extraction and storage process operates continuously throughout the content consumption period, rather than requiring discrete user actions. This continuous background processing ensures that information is captured consistently even when the user is engaged in other tasks, maintaining the completeness of knowledge construction while allowing multitasking to proceed.

Inventive Principle:

Principle #20Continuity of useful action

3Productivity

If traditional content analysis tools are used, then text outline generation is achieved, but pattern matching translation accuracy deteriorates due to information overload

Engineering Contradiction:

Improvecontent analysis efficiencyVSAvoidpattern matching translation accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent segments the content analysis process into distinct components: entity extraction, relationship identification, contextual information capture, and knowledge structure organization. This segmentation allows each component to focus on specific aspects of the content, improving the accuracy of pattern matching and translation by processing information in manageable, organized units rather than overwhelming the system with undifferentiated data.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system applies different processing qualities to different parts of the content based on their importance and characteristics. Critical entities and relationships receive more detailed extraction and validation, while less important information is processed more efficiently. This local quality approach optimizes both productivity and accuracy by allocating computational resources strategically across the content analysis task.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS11250086B2Visualization and augmentation of human knowledge construction during material consumption

Publication Date: 2022.02.15 TELEFONAKTIEBOLAGET LM ERICSSON (PUBL)

AI summary

Providing knowledge representation of material content being consumed by a user combines the user's current behavioral data and data from external sources such as internet web sites and social media network. Visual representations of entities and their relationships in the content being consumed by the user are created while the user is consuming content, and displayed via a graphical user interface.