Virtual Event Segmentation via Interaction Graphs
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Solution Overview
Problem
Virtual events face challenges in managing network traffic and user experience due to the large number of attendees, leading to inefficiencies and reduced interaction quality.
Innovation Solution
A system that intelligently segments attendees based on their interests and expertise using interaction graphs, reducing data transmission load and enhancing user engagement by placing similar users in smaller, more focused groups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data for every user's avatar is transmitted in a virtual event with thousands of attendees, then the user experience is enhanced through comprehensive data representation, but network bandwidth and processing power become insufficient
Solution Approach 1:
The patent segments attendees into groups based on interaction graphs and topic models, transmitting data only within segments rather than globally. This divides the large-scale virtual event into manageable sub-groups, reducing overall network traffic while maintaining user experience quality within each segment.
Solution Approach 2:
The patent applies local quality by transmitting detailed avatar data only to relevant users within the same segment,而非 universally to all users. This localized data transmission reduces network bandwidth consumption while preserving the quality of interactions for those who actually need the data.
2Measurement precision
If automated segmentation based on interaction graphs is implemented, then segmentation precision is improved, but computational load increases
Solution Approach 1:
The patent performs preliminary action by pre-computing interaction graphs and topic models before the virtual event begins. This advance processing allows the system to have segmentation ready beforehand, reducing real-time computational load during the actual event while maintaining high segmentation precision.
Solution Approach 2:
The system uses self-service by automatically generating interaction graphs and topic models from user data without requiring manual intervention. This automated approach improves segmentation accuracy while the system manages its own computational resources efficiently through iterative optimization.
3Productivity
If user segments are created based on multiple criteria, then user engagement is enhanced through meaningful interactions, but device complexity increases
Solution Approach 1:
The patent applies universality by using a multi-functional topic model that serves multiple purposes: it segments users, identifies relevant content, and optimizes interactions. This single multi-functional approach reduces overall system complexity compared to using separate specialized systems for each function.
Solution Approach 2:
The interaction graph serves as an intermediary structure that mediates between raw user data and segmentation decisions. This intermediate representation simplifies the complexity by providing a unified framework that captures user relationships, topics, and interactions in a structured manner.
Data Source
AI summary
The disclosed techniques improve the efficiency and functionality of virtual event platforms by segmenting users that attend a virtual event. An event segmenter retrieves user data for each attending user. The user data can include interaction data from past virtual events, topic data derived from user activity, social data defining the user's social relationships, etc. The event segmenter uses the user data to identify topics of interest for each user and generate an interaction graph for each user based on the topics of interest. The event segmenter uses the interaction graphs to generate user segments for the virtual event and assign each user to a user segment based on matching topics of interest. A model optimizer collects and analyzes user activity within each user segment to train the event segmenter to modify interaction graphs. In this way, the event segmenter can improve the virtual event segmentation process over time.