Event Summarization via Participant-Filtered Sub-Event Clustering
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Solution Overview
Problem
Existing event summarization systems struggle to effectively capture important moments from social media data streams, particularly in noisy and dynamic environments like Twitter, where messages from various observers with different backgrounds and non-standard language usage overwhelm traditional summarization methods, leading to incomplete or biased summaries that often overshadow less prominent sub-events.
Innovation Solution
An event summarization system that processes chronologically-ordered text messages to identify sub-events by filtering keywords, cleaning and tagging messages, and using agglomerative clustering and mixture models to distinguish between participant and background topics, enabling incremental summarization of sub-events during events, including those involving multiple participants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional summarization methods are used on social media data streams, then the processing speed is maintained, but the accuracy and completeness of event summaries deteriorate due to noisy and non-standard language usage
Solution Approach 1:
The patent segments the event summarization task into distinct phases: message collection, sub-event detection, participant identification, and summary generation. By dividing the complex processing into manageable segments, the system can apply specialized techniques to each phase, improving overall accuracy while maintaining manageable complexity.
Solution Approach 2:
The patent introduces intermediate processing steps including message filtering, keyword identification, and participant entity recognition that act as mediators between raw social media messages and final summaries. These intermediary processes clean and structure the noisy input data before summary generation, significantly improving summary accuracy.
2Reliability
If peak detection algorithms are used to identify sub-events, then the processing simplicity is maintained, but the reliability of sub-event identification deteriorates when key participants dominate the message volume
Solution Approach 1:
The patent applies local quality analysis by examining the content and context of messages from different participants individually, rather than treating all messages uniformly. This allows the system to identify sub-events based on local patterns in participant behavior and message content, improving reliability even when message volumes are dominated by key participants.
Solution Approach 2:
The patent implements dynamic participant identification that adapts to changing message patterns throughout the event. The system continuously updates its understanding of participant roles and message significance, allowing it to reliably identify sub-events even as message volumes and participant prominence change over time.
3Loss of information
If messages from multiple observers with different backgrounds are processed, then the comprehensiveness of event coverage is improved, but the difficulty of interpreting message meanings increases due to non-standard language usage
Solution Approach 1:
The patent transforms the parameter of message representation by converting diverse, non-standard social media messages into a standardized format with identified entities, keywords, and semantic categories. This parameter transformation maintains the comprehensiveness of information from diverse observers while making the data suitable for automated processing and interpretation.
4Loss of time
If real-time summarization is implemented during events, then the timeliness of information delivery is improved, but the quality of summaries deteriorates due to incomplete data availability
Solution Approach 1:
The patent performs preliminary processing of messages as they arrive, including filtering, keyword extraction, and participant identification, so that when sub-events are detected, the foundational analysis is already complete. This preliminary action enables rapid summary generation without sacrificing quality, as the heavy lifting of message analysis has already been performed.
Data Source
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AI summary
A method for processing messages pertaining to an event includes receiving a plurality of messages pertaining to the event from electronic communication devices associated with a plurality of observers of the event, generating a first message stream that includes only a portion of the plurality of messages corresponding to a first participant in the event, identifying a first sub-event in the first message stream with reference to a time distribution of messages and content distribution of messages in the first message stream, generating a sub-event summary with reference to a portion of the plurality of messages in the first message stream that are associated with the first sub-event, and transmitting the sub-event summary to a plurality of electronic communication devices associated with a plurality of users who are not observers of the event.