Targeted Media Playback Customization for User Tolerance Control
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Solution Overview
Problem
Existing media streaming systems fail to accommodate varying user preferences for the amount of targeted media content, leading to inconsistent viewing experiences.
Innovation Solution
A system and method that allows users to input their preferred level of exposure to targeted media content, using machine learning algorithms to customize the amount, frequency, and type of targeted media content based on user inputs and preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If targeted media content is added to media content items, then revenue and engagement are improved, but user satisfaction deteriorates when the amount of targeted content exceeds user tolerance
Solution Approach 1:
The system dynamically adjusts the amount and type of targeted media content inserted into media content items based on real-time user feedback and preferences. Users can specify their tolerance levels for targeted content, and the system adapts the content delivery accordingly, transitioning from static to dynamic content customization.
Solution Approach 2:
The system changes the parameters of targeted media content delivery by allowing users to define preference levels for different types of targeted content. The system then modifies the quantity, frequency, and variety of targeted content inserted into media content items based on these user-defined parameters, optimizing both revenue and user satisfaction.
2Productivity
If the amount of targeted media content is increased to maximize revenue, then advertising effectiveness is improved, but viewing experience consistency deteriorates
Solution Approach 1:
The system applies different qualities and amounts of targeted media content to different media content items based on user preferences. Instead of uniformly inserting targeted content across all content, the system customizes the targeted content insertion for each user and content item, creating local optimization rather than global uniformity.
Solution Approach 2:
The system performs preliminary actions by collecting user feedback and preferences before delivering targeted media content. Users indicate their tolerance levels in advance, and the system uses this pre-collected information to determine the appropriate amount and type of targeted content to insert, ensuring consistent viewing experiences from the outset.
3Object-affected harmful factors
If user feedback collection mechanisms are implemented to improve content customization, then user satisfaction is improved, but system complexity increases
Solution Approach 1:
The system implements self-service by allowing users to directly input their preferences and feedback regarding targeted media content. Users actively participate in defining their own content experience parameters, reducing the need for complex automated analysis systems while still achieving high levels of personalization.
Solution Approach 2:
The system incorporates feedback mechanisms where users indicate their preferences and tolerance levels for targeted media content. This feedback loop enables the system to continuously improve content customization based on user responses, enhancing satisfaction while maintaining manageable system complexity through direct user input.
Data Source
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AI summary
Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for processing, understanding, and defining media content. An example process can include receiving, from a media device, a user input indicative of a preferred level of exposure to targeted media content; configuring, based on the user input, one or more playback settings associated with a media content item to accommodate a customized amount of the targeted media content during playback of the media content item; and sending, to the media device, the media content item and the customized amount of the targeted media content.