Interactive Display Smart Triggers for Real-Time Content Relevancy
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Solution Overview
Problem
User interfaces often display irrelevant content, hindering user experience by obscuring essential information and reducing usability due to cluttered layouts.
Innovation Solution
A computer-implemented method and system that generates smart triggers in an interactive display by integrating real-time event data and user data to determine user-specific actions, such as market predictions, using machine-learning models to prioritize relevant content and reduce unnecessary computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If real-time event data and user data are integrated to generate personalized smart triggers, then user experience and content relevancy are improved, but computational overhead and processing complexity increase
Solution Approach 1:
The system pre-generates multiple potential trigger templates and categorizes user data beforehand. When real-time events occur, the system quickly matches events against pre-categorized data and templates rather than processing everything from scratch, significantly reducing real-time computational overhead while maintaining personalized relevancy
Solution Approach 2:
The computational process is divided into distinct modules: data collection module, real-time event processing module, trigger generation module, and display update module. Each module handles specific tasks independently, allowing for optimized resource allocation and parallel processing that reduces overall computational complexity
2Loss of information
If multiple triggers are displayed in the interactive interface, then information completeness is improved, but interface clutter and user experience deteriorate
Solution Approach 1:
Different trigger elements are assigned different visual priorities and display characteristics based on their relevancy scores. High-priority triggers receive prominent placement with larger visual weight, while lower-priority triggers are displayed more subtly or in less prominent locations. This creates a visually hierarchical interface that presents complete information without appearing cluttered
Solution Approach 2:
The system extracts and displays only the most relevant trigger elements that exceed a dynamically adjusted relevancy threshold. Less relevant triggers are either omitted from the current display or placed in an accessible but non-intrusive area, allowing the interface to remain clean and focused while preserving access to complete information
3Measurement precision
If real-time processing is implemented for all user data and event data, then trigger accuracy is improved, but processing speed and response time worsen
Solution Approach 1:
The system applies full real-time processing only to the most critical data elements that have the greatest impact on trigger accuracy, while using simplified processing rules for less critical data. This selective processing approach maintains high accuracy for key decisions while improving overall processing speed and system responsiveness
Data Source
AI summary
Techniques described herein relate to a computer-implemented method for generating smart triggers in an interactive display. The method may include receiving a plurality of real-time event data comprising a plurality of real-time event actions, receiving a plurality of user data comprising a plurality of user actions, capturing one or more real-time user interactions with the interactive display, generating a unique relevancy threshold using the plurality of real-time event actions, the plurality of user actions, and the one or more real-time user interactions, as the plurality of real-time event data and the one or more real-time user interactions are received, generating, in real-time, at least one unique smart trigger that may have a relevancy that exceeds the unique relevancy threshold, and updating, in real-time, the interactive display with the at least one unique smart trigger.