18383772. COMPUTING DEVICE AND OPERATING METHOD THEREOF simplified abstract (Samsung Electronics Co., Ltd.)

COMPUTING DEVICE AND OPERATING METHOD THEREOF

Organization Name

Samsung Electronics Co., Ltd.

Inventor(s)

Kwanki Ahn of Suwon-si (KR)

Saeeun Choi of Suwon-si (KR)

COMPUTING DEVICE AND OPERATING METHOD THEREOF - A simplified explanation of the abstract

This abstract first appeared for US patent application 18383772 titled 'COMPUTING DEVICE AND OPERATING METHOD THEREOF

Simplified Explanation

In this patent application, a computing device uses metadata information and content viewing history to generate personalized recommendations for a user. The device creates feature vectors based on the user's viewing history and metadata related to the content, then compares these vectors to recommend relevant content to the user.

• Computing device generates personalized recommendations for a user based on metadata and viewing history.
• Feature vectors are created using user's viewing history and content metadata.
• Recommendations are generated by comparing user's feature vector with feature vectors of content items.

Potential Applications

This technology could be applied in various industries such as:

• E-commerce platforms for suggesting products to users based on their browsing history.
• Streaming services for recommending movies or TV shows to viewers.
• Social media platforms for suggesting posts or profiles to users.

Problems Solved

This technology addresses the following issues:

• Providing personalized recommendations to users based on their preferences.
• Improving user engagement by suggesting relevant content.
• Enhancing user experience by tailoring recommendations to individual preferences.

Benefits

The benefits of this technology include:

• Increased user satisfaction by offering personalized recommendations.
• Higher user engagement and retention rates.
• Improved content discovery for users.

Potential Commercial Applications

Some potential commercial applications of this technology are:

• Personalized advertising platforms.
• Recommendation engines for online retailers.
• Content curation services for media companies.

Possible Prior Art

One possible prior art for this technology is the collaborative filtering algorithm used in recommendation systems, where user preferences are inferred from similar users' behavior to make recommendations.

How does the computing device handle privacy concerns when accessing user data for generating recommendations?

The patent application does not provide details on how user data privacy is maintained while generating personalized recommendations. It would be important to understand the measures in place to protect user information.

What is the computational complexity of generating recommendations for a large number of users and content items?

The patent application does not discuss the scalability of the recommendation system for a large dataset. Understanding the computational resources required for generating recommendations at scale would be crucial for practical implementation.

Original Abstract Submitted

A computing device obtains first metadata information related to a plurality of items of content and content viewing history information related to a user, generates a first feature vector for the user based on second metadata information related to at least one item of content viewed by the user in the content viewing history information related to the user, generates a plurality of second feature vectors, each of the plurality of second feature vectors corresponding to one of the plurality of items of content based on the first metadata information related to the plurality of items of content, and generate a recommendation including at least one item of content to the user, among the plurality of items of content, based on a result of a comparison between first feature vector for the user and the plurality of second feature vectors of the plurality of items of content.