Message Subscription Using Aggregate Characteristics
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Solution Overview
Problem
Conventional message subscription methods rely on keyword or originator-based subscriptions, which are limited in flexibility and often include irrelevant content, failing to provide users with messages tailored to their specific preferences.
Innovation Solution
A messaging system that allows users to create subscriptions based on message aggregate characteristics beyond textual and biographical information, such as demographic, geographical, emotional, and topical activity levels, enabling more precise filtering and relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If keyword or originator-based subscriptions are used, then the subscription system is simple to operate, but the relevance and flexibility of delivered messages deteriorates
Solution Approach 1:
The patent changes the subscription parameters from simple keywords or originators to multi-dimensional message aggregate characteristics including emotional tone, demographic information, geographical location, and topical activity levels. This allows users to subscribe based on complex composite parameters rather than single simple parameters, improving message relevance while maintaining operational simplicity through standardized subscription interfaces.
Solution Approach 2:
The patent creates composite subscription criteria by combining multiple message characteristics (emotional, demographic, geographical, topical) into a unified subscription model. Instead of relying on a single simple parameter, the system evaluates messages against composite profiles that aggregate multiple characteristics, thereby improving relevance while keeping the subscription mechanism unified and easy to operate.
2Manufacturing precision
If message subscriptions are based on multiple aggregate characteristics, then the relevance of delivered messages improves, but the complexity of the subscription system increases
Solution Approach 1:
The patent introduces intermediary components including a message characteristic extraction module that automatically derives aggregate characteristics from messages, and a subscription matching engine that handles the complex comparison logic. These intermediaries shield users from complexity by automatically performing multi-dimensional analysis and matching, allowing simple user-facing subscription interfaces while maintaining sophisticated relevance filtering in the background.
Solution Approach 2:
The patent segments the subscription system into distinct functional modules: message aggregation, characteristic extraction, subscription profile management, and message matching. Each module handles a specific aspect of the complex process independently, allowing the system to manage multiple aggregate characteristics without overwhelming complexity. Users interact with simplified module interfaces while the backend modules handle the sophisticated multi-parameter analysis.
3Device complexity
If conventional keyword-based filtering is used, then the system complexity is low, but the ability to filter irrelevant content deteriorates
Solution Approach 1:
The patent transforms the filtering parameters from simple keywords to comprehensive message aggregate characteristics including emotional tone, demographic alignment, geographical relevance, and topical activity metrics. This parameter transformation enables the system to filter out irrelevant content that would pass through keyword-based filters, while managing complexity through standardized evaluation frameworks and automated characteristic extraction.
Solution Approach 2:
The patent replaces mechanical keyword-matching filters with automated information processing systems that extract and evaluate multiple message characteristics simultaneously. Instead of simple string matching, the system uses computational analysis to derive emotional, demographic, geographical, and topical features, then applies sophisticated matching algorithms. This substitution increases filtering effectiveness while managing complexity through automation and standardized processing pipelines.
Data Source
AI summary
A method for message subscription based on a message aggregate characteristic is described. The method includes receiving a message subscription from a user. The message subscription is based on the message aggregate characteristic including an aspect other than textual content and bibliographic content. The method also includes determining a published message in response to receiving the message subscription. The published message satisfies the message aggregate characteristic. The method also includes providing an indication of the published message to the user.