AI Summary Creation Using Sentence Labels for Accurate Gist Extraction

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Solution Overview

Problem

Existing methods for creating summaries from documents, especially academic papers, are time-consuming and prone to inaccuracies due to reliance on human expertise, and existing automated methods struggle to accurately capture the gist of clusters.

Innovation Solution

A computer-based method involving sentence decomposition, label assignment, and summary element extraction using AI to create a highly accurate summary from one sentence.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If human experts manually analyze and create summaries of documents, then the accuracy and understanding of specialized content is improved, but the time consumption and labor cost increase significantly

Engineering Contradiction:

Improveaccuracy of summaryVSAvoidtime consumption

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent introduces an automatic summary creation system that acts as an intermediary between the original documents and the users. This system performs morphological analysis, extracts important words, creates vectors, and generates summaries automatically, eliminating the need for human experts to manually analyze each document while maintaining reasonable accuracy.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces the mechanical human analysis process with an automated computer-based system. The system uses morphological analysis, vectorization, and automatic extraction algorithms to substitute for human experts' manual reading, classification, and summary creation, significantly reducing time consumption.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If automated cluster analysis extracts important words by frequency weighting, then the processing speed is improved, but the accuracy of extracting gist words decreases due to noise

Engineering Contradiction:

Improveprocessing speedVSAvoidaccuracy of gist extraction

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent applies local quality by differentiating the treatment of different words within the cluster. Instead of uniform frequency weighting, the system identifies and emphasizes words that truly represent the cluster's gist while filtering out noise words, giving different importance levels to different positions and types of words within the cluster.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent changes the parameter for word importance from simple frequency count to a more sophisticated metric that considers both frequency and representativeness. The system adjusts weighting parameters to balance between common words and distinctive words, optimizing the extraction of meaningful gist words while reducing noise.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS12518085B2Summary creation method, summary creation system, and summary creation program

Publication Date: 2026.01.06 AIXS INC

AI summary

A server 4 executes a sentences decomposition step (S6) of decomposing one sentences into a sentence, a label assigning step (S7) of assigning a label according to content of the decomposed sentence, a summary element extracting step (S8) of extracting a sentence to which a predetermined label is assigned as a summary element, and a summary creation step (S9) of creating a summary based on the summary element.