Spontaneous Content Delivery Adaptation via User Reaction Feedback
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Solution Overview
Problem
Existing spontaneous content delivery systems lack personalization and adaptability, often transmitting content randomly and without user consent, leading to reduced effectiveness due to mismatched content formats and unmet user preferences.
Innovation Solution
A method for managing a set of parameters to deliver spontaneous content, which includes user-specific preferences, technical characteristics of the terminal, and contextual data to personalize and adapt content delivery, ensuring content is delivered at favorable times based on user reactions and interests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If spontaneous content is transmitted randomly to users without responding to user needs, then content can be delivered to a large number of users, but user receptivity diminishes and effectiveness is reduced
Solution Approach 1:
The system performs preliminary actions by collecting user preference data, terminal characteristics, and contextual information before content delivery. This advance preparation enables the system to predict favorable moments for content delivery and pre-select appropriate content, thereby improving user receptivity while maintaining delivery volume
Solution Approach 2:
The system dynamically changes delivery parameters including timing, content format, and content selection based on user preferences, terminal characteristics, and contextual data. This parameter adaptation ensures content is delivered at favorable moments in formats suitable for each user's device and interests, resolving the contradiction between delivery volume and user receptivity
2Ease of operation
If content is transmitted without user consent, then delivery can occur independently of user requests, but users may not be receptive to the transmitted content
Solution Approach 1:
The system implements feedback mechanisms by collecting user reactions, preferences, and interaction data. This feedback loop enables the system to learn from user responses and adjust future content delivery accordingly, maintaining automatic delivery while improving user receptivity through data-driven personalization
Solution Approach 2:
The system performs preliminary actions by obtaining user consent and collecting preference data before autonomous content delivery begins. This advance user engagement ensures that subsequent automatic deliveries are based on user-approved parameters, resolving the contradiction between ease of operation and user receptivity
3Productivity
If spontaneous content providers transmit content intended to correspond to the largest subset of users, then content can reach more users, but the content format and information do not match individual user preferences
Solution Approach 1:
The system segments the user base into individual profiles with distinct preferences, terminal characteristics, and contextual data. This segmentation enables the system to deliver content tailored to each user's specific characteristics while maintaining broad reach through personalized content selection and formatting for each segment
Solution Approach 2:
The system applies local quality by customizing content format, timing, and selection for each individual user based on their specific preferences and terminal characteristics. This user-specific adaptation allows the system to maintain high content reach while ensuring each user receives personally relevant content in an appropriate format
Data Source
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Figure 2a~3
AI summary
The method involves delivering content to a user, and detecting if the user generates a reaction favorable or unfavorable to the delivered content, on a terminal (5). A parameter representing the reaction of the user and a contextual parameter associated to the delivered content are stored in a set of parameters to adapt the parameters to exposed centers of interest of the user. Planning is established via the terminal for delivering selected spontaneous content from the adapted parameters to determine an instant suitable for delivering the selected content. Independent claims are also included for the following: (1) a method for delivering spontaneous content to a user of a terminal (2) a method for transmitting spontaneous content over a network (3) a terminal of a network, comprising a processing unit (4) a remote system comprising a processing unit.