Media Recommendation Channels via User Data Segmentation

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Solution Overview

Problem

Existing media systems face challenges in generating effective communications channels between devices based on user-related data to recommend media content that aligns with user interests, as they struggle to accurately collect and analyze user preferences and interactions.

Innovation Solution

A system that collects user data through various means, including sensors and user devices, to identify correlations between user interactions and media usage, ranking these correlations to recommend media content items based on user preferences and affinities, and initiates user-user interactions to enhance content recommendations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If the system collects and analyzes user data to generate communications channels for media recommendations, then content relevance and user engagement improve, but system complexity and data processing requirements increase

Engineering Contradiction:

Improvecontent recommendation accuracyVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent segments user data into multiple dimensions including user profiles, content metadata, interaction history, and contextual information. This segmentation allows the system to process and analyze different types of data separately, managing complexity while improving recommendation accuracy through multi-faceted user understanding

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces communication channels as intermediary structures that connect users with recommended content. These channels serve as mediators that organize and facilitate the flow of information between the complex data processing system and the user experience, making the system more adaptable without proportionally increasing perceived complexity

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If the system initiates user-user interactions based on media content, then user engagement increases, but the difficulty of detecting and measuring user preferences increases

Engineering Contradiction:

Improveuser engagementVSAvoidpreference detection difficulty

Core Design Contradiction:

ProductivityVSDifficulty of detecting and measuring

Solution Approach 1:

The patent implements feedback mechanisms where user interactions with media content and with other users are continuously collected and analyzed. This feedback loop allows the system to refine preference detection over time, enabling increased user engagement while systematically improving the accuracy of preference measurement through iterative learning

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent performs preliminary analysis of user data to identify potential preferences and interaction opportunities before actual user interactions occur. By pre-processing and pre-analyzing data to establish baseline preferences and predicted interaction patterns, the system reduces the difficulty of detecting preferences during live interactions while maintaining high engagement levels

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS12120193B2Communications channels in media systems

Publication Date: 2024.10.15 DISH TECHNOLOGIES LLC

AI summary

A computing device is programmed to receive, first and second user indicia of interest for media content. The computing device is further programmed to receive first user data related to a media content item. Based at least in part on the first and second user indicia of interest and the first user data, the computing device is further programmed to generate output that the first user recommend the media content item to the second user.