AI Event Summarization for Reducing Review Time
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Solution Overview
Problem
Conventional event management approaches require individuals to review entire event recordings to gather useful information, which is time-intensive and resource-intensive due to the mixing of sought-after information with noise and less relevant discussions.
Innovation Solution
The use of artificial intelligence techniques to automatically summarize event-related data, including text-based and non-text-based data, by generating content-related and participant sentiment-related summarizations, and performing automated actions based on these summarizations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional event management approaches record and make recordings available for offline playback, then event information is preserved and accessible, but individuals must view and listen to the entire duration of the event recording to gather useful information, which is time-intensive and resource-intensive
Solution Approach 1:
The patent extracts key information from event recordings by generating summaries that isolate important content from the full recording. The summarization system identifies and extracts relevant segments, key points, and essential information, allowing users to access only the extracted精华 without reviewing the entire recording.
Solution Approach 2:
The patent performs preliminary summarization of event recordings before users need to review them. By pre-processing the full recordings into condensed summaries with key information extracted and organized, the system eliminates the need for users to manually review entire events, significantly reducing their time investment.
2Loss of information
If conventional event management approaches make full recordings available, then complete event data is accessible, but the mixing of sought-after information with noise and less relevant discussions makes review resource-intensive
Solution Approach 1:
The system extracts relevant information from noisy full recordings by identifying and isolating key content. The summarization process filters out less relevant discussions and noise while preserving important information, delivering a refined subset of the complete event data that maintains productivity.
Solution Approach 2:
The patent applies different quality levels to different parts of the event recording. Instead of uniform treatment, the system identifies high-value segments and presents them with enhanced prominence in summaries, while less critical portions are condensed or omitted, creating a non-uniform information distribution that improves retrieval efficiency.
3Loss of time
If artificial intelligence techniques are used to generate content-related and participant sentiment-related summarizations, then time and resources needed to review event recordings are significantly reduced, but system complexity increases
Solution Approach 1:
The patent introduces an AI summarization system as an intermediary between the full event recording and the user. This intermediary layer handles the complex processing of generating content-related and sentiment-related summaries, shielding users from system complexity while delivering simplified, actionable insights that dramatically reduce review time.
Solution Approach 2:
The system replaces manual review processes with automated AI-based summarization. Instead of human users manually analyzing recordings, the patent employs machine learning models to automatically generate comprehensive summaries, substituting mechanical human effort with automated computational processes that reduce both time and resource requirements.
Data Source
AI summary
Methods, apparatus, and processor-readable storage media for automatically summarizing event-related data using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining text-based data and non-text-based data associated with at least one virtual event comprising one or more participants; generating a content-related summarization of one or more of at least a portion of the text-based data and at least a portion of the non-text-based data using at least a first set of one or more artificial intelligence techniques; generating a participant sentiment-related summarization associated with one or more of at least a portion of the text-based data and at least a portion of the non-text-based data using at least a second set of one or more artificial intelligence techniques; and performing one or more automated actions based at least in part on one or more of the content-related summarization and the participant sentiment-related summarization.