Connection Intention Analysis From Event Interaction Data

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Solution Overview

Problem

Traditional networking methods at social events are inefficient, leading to missed opportunities for meaningful connections due to lack of contextual insight, information overload, and incomplete network mapping, often relying on chance encounters without considering shared interests or compatibility.

Innovation Solution

Utilizing data analysis and machine learning techniques to process audio-visual feeds from events to determine interaction attributes and personal profiles, generating connection intentions and personalized recommendations based on shared interests, roles, and emotional analysis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If traditional networking methods are used at social events, then no additional system complexity is introduced, but networking efficiency is low and meaningful connections are missed

Engineering Contradiction:

Improvenetworking efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent introduces an intermediary system comprising audio-visual processing devices, data analysis systems, and machine learning models that act as mediators between participants at social events. This intermediary infrastructure processes interactions and generates connection suggestions, thereby improving networking efficiency without requiring direct complex interactions between individuals themselves.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces traditional manual networking mechanisms (face-to-face interactions, memory-based recall of contacts) with automated computational systems. Audio-visual feeds are processed by machine learning algorithms that analyze interaction attributes and generate connection recommendations, substituting mechanical human processes with electronic and algorithmic systems.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If data analysis of interaction information is performed, then connection intention determination accuracy is improved, but information processing complexity increases

Engineering Contradiction:

Improveconnection intention determination accuracyVSAvoiddata processing complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the complex data analysis process into distinct functional modules: audio processing, visual processing, interaction attribute extraction, personal profile analysis, and connection intention determination. Each module handles a specific aspect of the analysis, making the overall complex system more manageable and implementable through specialized components.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent performs preliminary actions by collecting and organizing personal profile information and interaction data before the actual connection intention determination. Audio-visual feeds are pre-processed to extract interaction attributes, and data is structured in advance, reducing the computational burden during real-time analysis and improving determination accuracy.

Inventive Principle:

Principle #10Preliminary action

3Adaptability or versatility

If audio-visual feed processing is implemented to determine interaction attributes, then interaction analysis capability is improved, but computational resources required increase

Engineering Contradiction:

Improveinteraction analysis capabilityVSAvoidcomputational resource consumption

Core Design Contradiction:

Adaptability or versatilityVSUse of energy by moving object

Solution Approach 1:

The patent applies partial action by selectively analyzing specific interaction attributes from audio-visual feeds rather than processing all possible data. The system focuses on extracting relevant interaction characteristics needed for connection intention determination, avoiding unnecessary computational overhead while maintaining adequate analysis capability.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS12530899B2Data analysis of interaction information for interacting participants to determine a connection intention

Publication Date: 2026.01.20 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

Provided are a computer program product, system, and method for data analysis of interaction information for interacting participants to determine a connection intention. An audio and/or a visual feed collected at an event is processed to determine whether interacting participants at the event are engaged in an interaction. A duration of the interaction, attributes of the interaction, and personal profile information of the interacting participants are determined. The duration of the interaction, the attributes of the interaction, and the personal profile information are processed to determine a connection intention indicating whether the interacting participants should connect or should not connect. Requests for the interacting participants to connect are transmitted in response to determining the connection intention indicates the interacting participants should connect.