{
  "patent_number": "US 11416536",
  "country": "US",
  "title": "How a Recommendation System Uses Dislikes to Suggest New Content",
  "original_title": "Content recommendation system",
  "summary": "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.",
  "what_it_does": "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).",
  "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."
  ],
  "filed": "2021-04-06",
  "granted": "2022-08-16",
  "expires": "2041-04-06",
  "status": "active",
  "holder": "Comcast Cable Communications",
  "holder_url": "https://patentbrief.org/company/comcast-cable-communications",
  "inventors": [
    {
      "name": "Zhen Zhao",
      "url": "https://patentbrief.org/inventor/zhen-zhao"
    }
  ],
  "times_cited": 3,
  "tags": [
    "software",
    "telecommunications",
    "consumer_electronics",
    "ai_ml",
    "ecommerce"
  ],
  "abstract": "Disclosed are systems and methods for determining similarities in content preferences among a plurality of users and generating content recommendations based on a requesting user's content consumption history. A requesting user may access the recommendation system to request content items for consumption. The recommendation system may be configured to identify users having consumed the same or similar content items as the requesting user, and to determine a ratio of content items consumed by the requesting user and an identified user to the total number of content items previously consumed by the requesting user. In one embodiment, the system may determine a degree of similarity in content preferences between the two users based on an inverse proportion of a level of popularity associated with the content items consumed by the requesting user and the identified user (e.g., sampled user).",
  "url": "https://patentbrief.org/patent/us/11416536/content-recommendation-system-11416536",
  "markdown_url": "https://patentbrief.org/patent/us/11416536/content-recommendation-system-11416536/md",
  "google_patents_url": "https://patents.google.com/patent/US11416536",
  "relatedPatents": []
}