Computing Device Connection Through Semantic Topic Matching
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Solution Overview
Problem
Existing technologies struggle to efficiently connect computing devices presenting similar information without manual intervention, leading to inefficiencies in resource usage and latency.
Innovation Solution
A software and/or hardware facility that constructs short-term and long-term interest profiles for computing devices based on captured audio and visual information, using semantic similarity tools to match and connect devices with similar topics, optimizing resource use and reducing latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual intervention is used to connect computing devices with similar information, then connection accuracy can be maintained, but resource usage efficiency deteriorates and latency increases
Solution Approach 1:
The system enables computing devices to automatically connect with similar devices through self-service mechanisms. The facility monitors information presented by devices, constructs interest profiles, and performs automatic matching without requiring manual intervention, thereby maintaining connection accuracy while improving resource efficiency
Solution Approach 2:
The system performs preliminary actions by constructing interest profiles in advance based on captured audio and visual information. By pre-processing and analyzing device information to create interest profiles before matching occurs, the system reduces latency and improves connection speed while maintaining accuracy
2Measurement precision
If manual intervention is used to connect computing devices with similar information, then connection accuracy can be maintained, but latency increases
Solution Approach 1:
The system maintains continuous monitoring and analysis of information presented by computing devices. By continuously capturing audio and visual information, constructing interest profiles in real-time, and continuously matching devices based on similarity, the system eliminates delays associated with manual intervention while maintaining connection accuracy
Solution Approach 2:
The system performs preliminary profile construction and similarity analysis in advance, before connection is actually needed. This pre-processing of device information into structured interest profiles enables rapid matching when connection requests occur, significantly reducing latency while preserving accuracy
3Measurement precision
If sophisticated matching algorithms are implemented to connect devices with similar topics, then connection precision improves, but device complexity increases
Solution Approach 1:
The system introduces an intermediary facility that handles the complex matching algorithms separately from the computing devices themselves. The facility acts as a mediator that receives information from devices, performs sophisticated similarity analysis using interest profiles, and facilitates connections, thereby improving matching precision without increasing complexity at the device level
Solution Approach 2:
The system extracts the complex matching functionality from the individual computing devices and places it in a separate centralized facility. By taking out the sophisticated algorithm processing from the devices and concentrating it in the facility, the system achieves high precision topic matching while keeping device complexity low
Data Source
AI summary
A facility for connecting devices is described. The facility recurringly captures information presented by the distinguished device, each time generating a summary. The facility determines a short-term interest profile for the distinguished device based on summaries generated for information captured a first trailing window, and determines a long-term interest profile for the distinguished device based on summaries generated for a longer second trailing window. For one or more devices other than the distinguished device, the facility: (1) determines a short-term similarity measure between the distinguished device's short-term interest profile and one determined for the other subject device; (2) determines a long-term similarity measure between the distinguished device's long-term interest profile and one determined for the other subject device; and (3) based on the determined similarity measures, determines whether to match the distinguished device and the other device.