Expert Identification System for Collaboration Sessions
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Solution Overview
Problem
In collaboration sessions, identifying and inviting an expert participant in real-time based on the subject matter is challenging due to the lack of efficient systems for detecting relevant participants and content analysis.
Innovation Solution
A system that detects the subject matter of a collaboration session, identifies potential experts from user profiles, and invites them to join using a network of interconnected devices and servers, incorporating modules for content recognition, profile management, and rating systems to facilitate expert participation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual identification of experts is used during collaboration sessions, then participant control is maintained, but time consumption and efficiency deteriorate
Solution Approach 1:
The system performs preliminary actions by pre-analyzing collaboration session content (audio, video, text) to identify potential experts before they are needed. The content analysis module continuously processes session materials and the expert identification module maintains a ready pool of potential experts, so when an expert is needed, the identification and invitation process is already prepared and can execute quickly.
Solution Approach 2:
The patent replaces the manual mechanical process of expert identification with an automated information processing system. The content analysis module uses audio recognition, video analysis, and text processing to automatically identify subjects matter and match them with expert profiles, substituting human manual searching and selection with automated computational analysis.
2Productivity
If automated expert identification system is implemented, then efficiency is improved, but system complexity increases
Solution Approach 1:
The system is divided into distinct functional modules: content analysis module (with audio, video, and text analysis components), expert identification module, profile management module, and invitation module. Each module has a specific function and can be independently developed, tested, and maintained, reducing overall system complexity while enabling automated expert identification.
Solution Approach 2:
The patent introduces intermediary components such as the subject matter extraction module that acts as a bridge between content analysis and expert identification, and the profile database that mediates between expert criteria and potential expert matches. These intermediaries simplify the interaction between complex modules by providing standardized interfaces and data formats.
3Measurement precision
If real-time content analysis is performed, then expert identification accuracy is improved, but computational resources and processing time increase
Solution Approach 1:
The system performs partial content analysis by focusing on key indicators and representative samples rather than analyzing every detail of collaboration session content. The content analysis module selectively processes audio transcripts, video key frames, and text documents to identify subject matter, using targeted analysis rather than exhaustive processing to reduce computational overhead while maintaining accuracy.
Solution Approach 2:
The patent implements continuous but optimized content analysis during collaboration sessions. Rather than performing intensive batch processing, the system continuously monitors content with optimized algorithms that maintain accuracy while reducing peak computational demands, allowing real-time expert identification without excessive resource consumption.
Data Source
AI summary
In one embodiment, the methods and apparatuses include requesting an expert during a collaboration session; determining a subject matter of the collaboration session; detecting a potential participant to serve as the expert; and inviting the potential participant to join the collaboration session.