Meta platforms technologies, llc (20240098341). USER-CENTRIC RANKING ALGORITHM FOR RECOMMENDING CONTENT ITEMS simplified abstract
Contents
- 1 USER-CENTRIC RANKING ALGORITHM FOR RECOMMENDING CONTENT ITEMS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 USER-CENTRIC RANKING ALGORITHM FOR RECOMMENDING CONTENT ITEMS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
USER-CENTRIC RANKING ALGORITHM FOR RECOMMENDING CONTENT ITEMS
Organization Name
meta platforms technologies, llc
Inventor(s)
Shuanghong Yang of Cupertino CA (US)
USER-CENTRIC RANKING ALGORITHM FOR RECOMMENDING CONTENT ITEMS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240098341 titled 'USER-CENTRIC RANKING ALGORITHM FOR RECOMMENDING CONTENT ITEMS
Simplified Explanation
The abstract describes a method for requesting recommendations for content items in a recommender system. The method involves extracting a user attribute, identifying content items that match the user's preference, determining interest values for the user on each content item, and providing the user with a ranked list of content items based on their interest value.
- User attribute extraction
- Matching content items to user preferences
- Calculating interest values based on user and content item attributes
- Providing a ranked list of content items to the user
Potential Applications
This technology could be applied in various recommendation systems such as e-commerce platforms, streaming services, social media platforms, and online content platforms.
Problems Solved
This technology helps users discover relevant content items based on their preferences, improving user experience and engagement with the platform.
Benefits
- Personalized recommendations for users - Increased user satisfaction and engagement - Efficient content discovery process
Potential Commercial Applications
- E-commerce platforms - Streaming services - Social media platforms - Online content platforms
Possible Prior Art
One possible prior art for this technology could be collaborative filtering algorithms used in recommendation systems, where user preferences are inferred based on similar users' behavior.
Unanswered Questions
How does the method handle user privacy and data security?
The article does not address how user data is handled and protected within the recommender system. This is an important aspect to consider, especially with the increasing concerns around data privacy and security.
What are the potential limitations of the method in providing accurate recommendations?
The article does not discuss any potential limitations of the method, such as biases in the recommendation algorithm or challenges in accurately determining user preferences. Understanding these limitations is crucial for optimizing the performance of the recommender system.
Original Abstract Submitted
a method for requesting a recommendation for content items in a recommender system is provided. the method includes extracting a user attribute from the recommender system, identifying multiple content items that match a user preference based on the user attribute, determining an interest value for the user on each content item based on an affinity between the user attribute and a content item attribute, and providing the user a list of content items ranked according to the interest value for the user. a system including a memory storing instructions and a processor configured to execute the instructions and cause the system to perform the above method is also provided.
