Icebreaker People Highlight Selection via Rarity Thresholds
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Solution Overview
Problem
Existing technologies lack the ability to programmatically determine and present icebreaker information that is rare among a target group but common among a larger reference group, or vice versa, in personal computing devices, leading to inefficient manual configuration and limited dynamic presentation of contextual information during meetings or communications.
Innovation Solution
A system that determines a target group and a reference group, calculates the frequency of data feature values within the target group, and presents icebreaker information based on a rarity threshold, allowing for dynamic and automated selection of unique or shared features among users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual configuration is used to compare user data fields, then icebreaker information can be presented, but the system lacks adaptability and requires continuous manual assessment for each new field
Solution Approach 1:
The system automatically discovers and surfaces icebreaker people highlights by programmatically determining new types of information items that are common to a set of individuals but rare in the broader population. This self-service approach eliminates the need for manual assessment of each new data field while maintaining adaptability to user data structures.
Solution Approach 2:
The system dynamically adjusts the rarity threshold parameter to control what constitutes an icebreaker highlight. By changing this parameter, the system can adapt to different contexts and data types without requiring manual reconfiguration, resolving the contradiction between adaptability and complexity.
2Productivity
If manual configuration is used to specify data comparisons, then icebreaker information can be presented, but the process is inefficient and time-consuming
Solution Approach 1:
The system performs automatic discovery of icebreaker information without requiring human intervention. It programmatically analyzes user data, identifies rare commonalities, and presents highlights autonomously, dramatically improving productivity while eliminating the time investment required for manual configuration.
Solution Approach 2:
The system pre-computes and caches user profile data and commonalities in advance, so that when users interact, icebreaker information is immediately available without real-time processing delays. This preliminary action enhances productivity while minimizing perceived time loss.
3Loss of information
If conventional technology is used, then basic user profile information can be displayed, but the system cannot programmatically determine rare information items common to specific user groups
Solution Approach 1:
The system replaces manual mechanical processes of information assessment with automated computational algorithms. These algorithms programmatically determine rare information items common to user groups by analyzing data structures and calculating statistical rarity, thereby preserving high information value while achieving full automation.
Solution Approach 2:
The system uses feedback from user interactions and data patterns to continuously improve its identification of rare commonalities. By monitoring which information items are most valuable as icebreakers, the system refines its automated determination process, maintaining high information value while increasing automation capability.
Data Source
AI summary
Technology is disclosed for selecting at least one icebreaker people highlight, with respect to a person of interest in a target group, to be shown on one or more user devices. The target group is determined, along with a set of feature values in common among the target group. Similarly, a reference group related to the target group is determined, along with a set of feature values for the reference group. For each feature value in the set of common target group feature values, a frequency of the feature value with respect to the determined reference group is determined. Based on the determined frequency, at least one icebreaker people highlight from the determined set of feature values in common among the target group is caused to be presented on the user device.