Collaboration Model Generation from Request-Action Correlations

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Solution Overview

Problem

Users face challenges in identifying effective collaboration partners due to the complexity of online communications, where it is difficult to determine how requests for assistance are perceived by other users, leading to inefficiencies in finding beneficial collaborations.

Innovation Solution

A method that analyzes user-initiated interaction requests and subsequent actions to generate a collaboration model, providing real-time recommendations based on correlations between user requests and recipient responses, using statistical models to identify trends and predict successful collaborations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If users manually analyze online communications to identify collaboration partners, then collaboration effectiveness can be improved, but time consumption and complexity increase significantly

Engineering Contradiction:

Improvecollaboration effectivenessVSAvoidtime to identify partners

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system enables automated self-service by having the platform automatically analyze communication patterns, extract correlations between requests and actions, and generate collaboration recommendations without requiring manual user intervention. The processor automatically performs the analysis of electronic communications and generates the collaboration model.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical analysis of communications with an automated computational system. The processor uses statistical models and pattern recognition algorithms to analyze communication data, substituting human manual effort with automated information processing capabilities.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If users manually analyze online communications to identify collaboration partners, then collaboration effectiveness can be improved, but system complexity increases

Engineering Contradiction:

Improvecollaboration effectivenessVSAvoidanalysis system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system achieves universality by creating a multi-functional platform that simultaneously performs communication analysis, pattern recognition, statistical modeling, and collaboration recommendation generation. This consolidated approach reduces overall system complexity compared to separate specialized systems.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent introduces a processor-based intermediary system that mediates between raw communication data and user decision-making. This intermediary automatically processes and structures the complex communication patterns into actionable collaboration recommendations, simplifying the user interface while maintaining analytical depth.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Measurement precision

If real-time analysis of communication patterns is performed, then collaboration recommendations accuracy is improved, but processing resources are consumed

Engineering Contradiction:

Improverecommendation accuracyVSAvoidprocessing resource consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The system applies partial action by focusing analysis on specific correlation patterns between requests and actions rather than processing all possible communication attributes. This selective approach maintains recommendation accuracy while reducing unnecessary processing of irrelevant data elements.

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The patent implements preliminary action by pre-processing and structuring communication data as it is generated, organizing patterns and correlations in advance. This preliminary organization reduces the computational burden during real-time recommendation generation, as the data is already structured for analysis.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS10748194B2Collaboration group recommendations derived from request-action correlations

Publication Date: 2020.08.18 KYNDRYL INC

AI summary

In response to a user-initiated interaction request sent by a user using an electronic communication, subsequent actions performed by other users that received the user-initiated interaction request are analyzed. A determination is made as to whether the subsequent actions performed by the other users that received the user-initiated interaction request correlate to an intended interaction result of the user-initiated interaction request. A visual representation of a collaboration model that correlates probabilities of successful collaborations between the user and the other users is generated in accordance with determined correlations between the subsequent actions performed by the other users and the intended interaction result. A collaboration recommendation based upon a degree of correlation between the subsequent actions performed by the other users and the intended interaction result represented within the collaboration model is provided in association with the visual representation of the collaboration model.