Dynamic Confidence Level for Event Information Dissemination
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Solution Overview
Problem
Existing systems lack an effective method to dynamically adjust the dissemination of information related to events based on a confidence level, which affects how information is provided and influenced by events, particularly in response to new data or user interactions.
Innovation Solution
A method that determines an event confidence level from user messages and adjusts the dissemination of information based on this level, incorporating additional data from subsequent messages or user actions to influence search results, query suggestions, and notifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If information dissemination is based on static event detection, then system simplicity is maintained, but information relevance and user engagement deteriorate
Solution Approach 1:
The patent implements dynamic adjustment of information dissemination based on changing confidence levels. The system transitions from static event detection to dynamic confidence-based filtering, where the confidence level for each event is continuously updated as new messages are received, allowing the system to adapt its information dissemination strategy in real-time
Solution Approach 2:
The patent changes the parameter used for information dissemination from a binary event detection to a continuous confidence level parameter. By using confidence levels that can take various values between 0 and 1, the system can dynamically adjust the threshold for displaying event information, thereby controlling information flow based on the accumulated evidence from multiple messages
2Measurement precision
If event confidence level is determined from single message, then processing speed is maintained, but measurement precision deteriorates
Solution Approach 1:
The patent performs preliminary event detection from the first message to establish an initial confidence level, then continues to update this confidence level as additional messages arrive. This allows the system to provide timely initial responses while progressively improving measurement precision through accumulated evidence
Solution Approach 2:
The patent implements continuous updating of event confidence levels as new messages are received. Rather than performing discrete re-evaluations, the system continuously refines the confidence level based on the accumulating evidence stream, maintaining both responsiveness and precision
3Reliability
If information dissemination is influenced by low confidence events, then information completeness is improved, but information quality deteriorates
Solution Approach 1:
The patent uses confidence level as a dynamic parameter to control information dissemination. By adjusting the confidence threshold based on the specific event and context, the system can selectively filter information to maintain quality while preserving completeness for events that meet the reliability criteria
Data Source
AI summary
Methods and apparatus related to determining an effect on dissemination of information related to an event based on a dynamic confidence level associated with the event. For example, an event and an event confidence level of the event may be determined based on a message of a user. An effect on dissemination of information related to the event may be determined based on the confidence level. A new confidence level may be determined based on additional data associated with the event and the effect on dissemination of information may be adjusted based on the new confidence level. In some implementations, the additional data may be based on a new message that is related to the message, such as a reply to the message.