How a Recommendation System Uses Dislikes to Suggest New Content
Comcast's patent describes a content recommendation system that finds users with similar tastes by focusing on what content they both dislike, especially popular disliked items, to suggest new shows or movies.
Original patent title: “Content recommendation system”
Comcast's patent describes a content recommendation system that finds users with similar tastes by focusing on what content they both dislike, especially popular disliked items, to suggest new shows or movies. Granted to Comcast Cable Communications in 2022 with 24 claims and 3 forward citations, and it is expected to expire in 2041.
Coverage
What does this patent actually cover?
This patent describes a system that recommends content by finding users who share similar dislikes. First, it identifies a "target user" and a group of "candidate users." For each candidate user, the system determines how many content items both the candidate and the target user have disliked (ClaimclaimA numbered sentence at the end of a patent that legally defines what the inventor owns. The most important section.Read more → 1). The system then ranks these candidate users, giving more importance to commonly-disliked items that are popular among other users (Claim 1, 3, 5, 6). For instance, if you and another user both disliked a widely popular movie, that shared dislike would count more towards finding you a good recommendation than if you both disliked a very obscure film. Finally, the system suggests new content to the target user based on what the highest-ranked, similarly-disliking candidate users have consumed, ensuring the target user has not seen it before (Claim 4).
The gap
What does this patent NOT cover?
- Recommendation systems that only consider content a user has liked or consumed, without factoring in dislikes.
- Systems that do not give preference to commonly-disliked content items based on their overall popularity.
- Recommendation methods that rely solely on explicit user ratings without comparing shared disliked items.
- Systems that use a simple count of shared disliked items without weighting them by how popular those items are.
- Recommendations based purely on content metadata or genre similarity without user preference analysis.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
Key facts
What made this novel
The clever part is identifying user similarity not just by what they like or consume, but by what they *dislike*, and specifically, giving more weight to shared dislikes of *popular* content. This helps the system find more meaningful connections between users by focusing on strong, shared negative opinions about mainstream content.
The Patent Drawing
Schematic visualization of the patent's claim structure. Hand-drawn diagrams in progress for each landmark patent.
Where you've seen this
Real-world examples
Netflix recommendation engine
YouTube video suggestions
Amazon Prime Video recommendations
Hulu personalized content feeds
Spotify music discovery algorithms
Comcast Xfinity content recommendations
Why it matters
The bigger picture
Content recommendation systems are crucial for modern media platforms, helping users discover new content and keeping them engaged. This patent's approach to using shared dislikes, particularly popular ones, offers a refined way to identify user preferences. It aims to improve the accuracy of recommendations, which can increase user satisfaction and content consumption on platforms like those offered by Comcast.
Filed
April 6, 2021
Granted
August 16, 2022
Market context
Who's building on this
Companies in this space
Comcast Cable Communications, the assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →, is a major player in content delivery and streaming services, actively developing and deploying recommendation systems for its Xfinity platform. Other large streaming and media companies like Netflix, Amazon, and Google (YouTube) continuously refine their recommendation algorithms, often exploring various methods to enhance user engagement and content discovery.
Market impact
This patent contributes to the ongoing evolution of content recommendation systems, which are foundational to the success of streaming services and digital media platforms. By focusing on shared dislikes, it offers a distinct method for identifying user preferences, potentially leading to more precise recommendations. Such advancements can help companies like Comcast reduce subscriber churn, increase viewing times, and differentiate their service in a competitive market.
Claim 1 — Plain English
What this patent covers
This patent describes a system that recommends content by finding users who share similar dislikes. First, it identifies a "target user" and a group of "candidate users." For each candidate user, the system determines how many content items both the candidate and the target user have disliked (Claim 1). The system then ranks these candidate users, giving more importance to commonly-disliked items that are popular among other users (Claim 1, 3, 5, 6). For instance, if you and another user both disliked a widely popular movie, that shared dislike would count more towards finding you a good recommendation than if you both disliked a very obscure film. Finally, the system suggests new content to the target user based on what the highest-ranked, similarly-disliking candidate users have consumed, ensuring the target user has not seen it before (Claim 4).
The clever bit
The clever part is identifying user similarity not just by what they like or consume, but by what they *dislike*, and specifically, giving more weight to shared dislikes of *popular* content. This helps the system find more meaningful connections between users by focusing on strong, shared negative opinions about mainstream content.
What it does not cover
- Recommendation systems that only consider content a user has liked or consumed, without factoring in dislikes.
- Systems that do not give preference to commonly-disliked content items based on their overall popularity.
- Recommendation methods that rely solely on explicit user ratings without comparing shared disliked items.
- Systems that use a simple count of shared disliked items without weighting them by how popular those items are.
- Recommendations based purely on content metadata or genre similarity without user preference analysis.
Patent timeline
Application submitted to the patent office
Application published, typically 18 months after filing
Patent officially issued
Patent enters public domain
PatentBrief Score
Impact Score
Moderate
Citation count
12/40
Early citations
Claim breadth
16/20
Broad claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more →
Recency
20/20
Granted within 5 years
Assignee scale
0/20
Independent or smaller assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →
PatentBrief Impact Score — based on citation count, claim breadth, recency, and assignee scale. Not a legal assessment.
Heuristic Value Estimate
What this patent might be worth
$75K – $240K
Midpoint $150K · 14.6 yr remaining · industry ×1.6
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
Claim text not yet imported for this patent
The original legal language
Original claims
24 claims as filed with the patent office.
Concepts involved
Citations
Patent lineage
Cite this patent
Zhao, Z. (2022). How a Recommendation System Uses Dislikes to Suggest New Content (U.S. Patent No. 11,416,536). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/11416536/content-recommendation-system-11416536
Auto-generated from the patent record. Double-check author order and the issue date against the official USPTO document before submitting.
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Common Questions
Frequently Asked Questions
What does How a Recommendation System Uses Dislikes to Suggest New Content cover?
Comcast's patent describes a content recommendation system that finds users with similar tastes by focusing on what content they both dislike, especially popular disliked items, to suggest new shows or movies.
Who owns patent US 11416536?
Comcast Cable Communications owns this patent, granted in 2022.
When does this patent expire?
This patent is expected to expire on April 6, 2041, when the invention enters the public domain.
What is patent US 11416536 cited by?
This patent has been cited by 3 later patents that build on its ideas.
What problem does this patent solve?
Content recommendation systems are crucial for modern media platforms, helping users discover new content and keeping them engaged. This patent's approach to using shared dislikes, particularly popular ones, offers a refined way to identify user preferences. It aims to improve the accuracy of recommendations, which can increase user satisfaction and content consumption on platforms like those offered by Comcast.
What does this patent NOT cover?
Recommendation systems that only consider content a user has liked or consumed, without factoring in dislikes.
Same assignee
More from Comcast Cable Communications
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