Topic Segmentation via Conceptual Similarity and Consistency Metrics
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for segmenting content, such as debates, into smaller topics are tedious and time-consuming, especially for long content, leading to delays in streaming or uploading, and often result in differing topic segmentation points among operators.
Innovation Solution
A method and device that preprocess text data to calculate conceptual similarity and consistency metrics, allowing for automatic segmentation of topics by determining segmentation points based on similarity cohesion, enabling user-centered intervention and efficient processing of long content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual topic segmentation is performed by operators, then topic segmentation can be done, but it is tedious and time-consuming, causing delays in streaming or uploading
Solution Approach 1:
The system performs automatic topic segmentation without requiring manual intervention from operators. The automated algorithm processes content, identifies topics, and determines segmentation points independently, eliminating the tedious manual work while maintaining segmentation quality.
Solution Approach 2:
The patent replaces the mechanical manual segmentation process with an automated computational system. The system uses algorithms to analyze content, calculate conceptual similarity, and automatically divide topics, substituting human labor with machine processing to significantly reduce time consumption.
2Productivity
If automatic topic segmentation is implemented, then segmentation speed increases, but determining consistent segmentation points across different operators becomes difficult
Solution Approach 1:
The system uses adjustable parameters including conceptual similarity thresholds, consistency metrics, and weighting factors that can be modified based on content type and operator requirements. This allows the same automated system to produce consistent results across different operators by tuning parameters to match specific segmentation criteria.
Solution Approach 2:
The system incorporates consistency metrics that provide feedback on segmentation quality and comparability across different operators. By monitoring and adjusting segmentation results based on this feedback, the system ensures reliable and consistent topic segmentation points while maintaining high processing speed.
3Ease of operation
If detailed topic segmentation is performed, then content can be divided into smaller units for better viewing, but the process becomes cumbersome and time-consuming
Solution Approach 1:
The automated system performs detailed topic segmentation without requiring operator intervention. It independently analyzes content, identifies meaningful topics, and creates navigation-friendly segments, making the process both detailed and efficient simultaneously.
Solution Approach 2:
The system performs preliminary processing and segmentation automatically before content is made available for viewing. By pre-dividing content into topic segments with appropriate navigation markers, the system prepares the content for easy user access without requiring additional manual processing time.
Data Source
AI summary
A method of segmenting topics of content according to an embodiment is configured to preprocess text data configured of content, and divide a plurality of utterances into two topic segmented bodies based on the preprocessed data. The preprocessing may be performed by processing the text data in a continuous form of the plurality of utterances, and calculating a conceptual similarity between utterances based on the processed data. The topic segmented bodies may be divided into two by calculating similarity cohesion for the two topic segmented bodies based on the conceptual similarity and a consistency metric while changing a segmentation point which distinguishes the two topic segmented bodies, and determining the segmentation point based on the similarity cohesion.