Messaging Interface Control via Predicted Interaction Models

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Solution Overview

Problem

Conventional messaging systems inefficiently present messages based on date received, leading to messages that users are best suited to interact with being buried and causing excessive resource usage and forgotten interactions.

Innovation Solution

Generating an expected action model from message interactions and attributes to predict interactions, allowing for a graphical user interface to be controlled and present messages in a contextually relevant manner, prioritizing messages suited for interaction based on user context such as time and location.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If messages are presented based on date received, then the messaging system is simple to implement, but relevant messages become buried and users experience increased time loss

Engineering Contradiction:

Improvemessage presentation simplicityVSAvoidtime to find relevant messages

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The system performs preliminary analysis of messages by extracting attributes and predicting interactions before presenting them to the user. An expected action model is generated in advance based on historical interactions, allowing messages to be pre-sorted and highlighted according to predicted user needs, thus reducing the time users spend searching for relevant messages.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously learns from actual user interactions with messages to refine the expected action model. By monitoring real user behavior patterns and comparing them against predicted interactions, the system improves its message prioritization algorithm over time, making the presentation increasingly effective at surfaceing relevant messages while maintaining operational simplicity.

Inventive Principle:

Principle #23Feedback

2Device complexity

If conventional date-based message presentation is used, then system complexity is low, but user interaction accuracy decreases

Engineering Contradiction:

Improvesystem implementation complexityVSAvoiduser interaction accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The system segments the message presentation task into multiple components: attribute extraction, interaction prediction, and presentation generation. This segmentation allows each component to be developed and optimized independently, managing overall system complexity while improving the precision of user interaction predictions through specialized processing of message attributes and user behavior patterns.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The expected action model serves as an intermediary between raw message data and user interface presentation. This intermediary layer processes and interprets message attributes through the lens of historical interaction patterns, translating complex data into predicted user actions, thereby improving interaction accuracy without requiring direct complex processing at the user interface level.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Loss of information

If all messages are presented to users, then information completeness is maintained, but resource consumption increases

Engineering Contradiction:

Improvemessage information completenessVSAvoidresource consumption

Core Design Contradiction:

Loss of informationVSUse of energy by moving object

Solution Approach 1:

Instead of processing and presenting all messages equally (excessive action), the system applies partial action by selectively processing and highlighting only the subset of messages predicted to be most relevant to the user based on the expected action model. This partial processing approach reduces computational resource consumption while maintaining information completeness for the most important messages.

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The system changes the parameter of message presentation from uniform treatment to differentiated treatment based on predicted interaction likelihood. By adjusting presentation parameters (such as highlighting, ordering, or grouping) according to the expected action model, the system efficiently allocates resources to process and present only the most relevant messages, reducing overall resource consumption while preserving critical information.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS11714522B2Controlling a graphical user interface using a presentation of messages based upon predicted interactions with the messages

Publication Date: 2023.08.01 YAHOO ASSETS LLC

AI summary

One or more computing devices, systems, and/or methods for controlling a graphical user interface using a presentation of messages based upon predicted interactions with the messages are provided. For example, a plurality of messages associated with the messaging account may be received. Interactions with the plurality of messages may be tracked to generate sets of message interactions. The plurality of messages may be analyzed to identify sets of attributes. An expected action model may be generated based upon the sets of message interactions and the sets of attributes. A set of messages associated with the messaging account may be analyzed based upon the expected action model to predict one or more interactions corresponding to one or more potential presentations of the set of messages. A presentation may be selected from the one or more potential presentations. A graphical user interface may be controlled using the presentation.