Attention Score Vectors for Organizational Telemetry Discovery
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Solution Overview
Problem
Existing organization communication systems face challenges in assessing usage, impact, and value due to deficiencies in tracking and analyzing user interactions and organizational telemetry data.
Innovation Solution
The development of an apparatus that generates attention score vectors and interfaces within a group-based communication system, allowing for the discovery and presentation of organizational telemetry data. This apparatus calculates user priority scores, normalizes them, and generates attention scores to represent interaction likelihoods between users, which are then visualized in attention score interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional communication systems track and analyze user interactions, then usage assessment capability is improved, but data processing time and memory requirements increase
Solution Approach 1:
The patent segments the analysis by generating separate attention score vectors for different users, where each vector contains attention scores for their interactions with other users. This segmentation allows parallel processing of user interaction data, reducing overall processing time while maintaining comprehensive usage assessment capability.
Solution Approach 2:
The system performs preliminary actions by pre-calculating and storing attention score vectors for each user based on their interaction history. These pre-computed vectors are then readily available for quick retrieval and analysis, eliminating the need for real-time computation during usage assessment and significantly reducing data processing time.
2Measurement precision
If traditional communication systems track and analyze user interactions, then usage assessment capability is improved, but memory requirements increase
Solution Approach 1:
The patent extracts only the essential interaction data needed for usage assessment by generating attention score vectors that contain normalized attention scores for each user pair. This extraction approach stores only the most relevant interaction metrics rather than complete interaction histories, significantly reducing memory requirements while preserving usage assessment capability.
Solution Approach 2:
The system transforms raw interaction data into normalized attention scores through parameter changes. By converting absolute interaction counts into normalized scores that represent interaction likelihood, the system reduces data complexity and storage requirements while maintaining the ability to assess usage patterns effectively.
3Measurement precision
If the system generates detailed attention score vectors for multiple users, then interaction analysis precision is improved, but device complexity increases
Solution Approach 1:
The patent implements a universal attention score generation mechanism that can be applied to any user in the communication system. The same normalization and calculation processes are used across all users, creating a multi-functional system that handles diverse interaction scenarios with a unified approach, thereby managing complexity while maintaining precision.
Solution Approach 2:
By transforming complex interaction data into standardized attention score parameters, the system simplifies the representation of user interactions. The normalization process converts various interaction types into comparable numerical scores, reducing the complexity of analyzing diverse interaction patterns while preserving analytical precision.
Data Source
AI summary
Embodiments of the present disclosure provide methods, systems, apparatuses, and computer program products for discovery of organizational telemetry within a group-based communication system and rendering representations thereof.