View source for Samsung electronics co., ltd. (20240323464). METHOD OF TRACING KNOWLEDGE LEVEL OF USER CONSUMING CONTENT AND RECOMMENDING CONTENT BASED ON KNOWLEDGE LEVEL OF USER, AND COMPUTING DEVICE EXECUTING THE SAME simplified abstract

=METHOD OF TRACING KNOWLEDGE LEVEL OF USER CONSUMING CONTENT AND RECOMMENDING CONTENT BASED ON KNOWLEDGE LEVEL OF USER, AND COMPUTING DEVICE EXECUTING THE SAME=


==Organization Name==

[[:Category:samsung electronics co., ltd.|samsung electronics co., ltd.]]


[[Category:samsung electronics co., ltd.]]

==Inventor(s)==

[[:Category:Sungmok Seo of Suwon-si (KR)|Sungmok Seo of Suwon-si (KR)]][[Category:Sungmok Seo of Suwon-si (KR)]]

[[:Category:Taehun Kim of Suwon-si (KR)|Taehun Kim of Suwon-si (KR)]][[Category:Taehun Kim of Suwon-si (KR)]]

[[:Category:Jaebok Lee of Suwon-si (KR)|Jaebok Lee of Suwon-si (KR)]][[Category:Jaebok Lee of Suwon-si (KR)]]

[[:Category:Hyunkook Cho of Suwon-si (KR)|Hyunkook Cho of Suwon-si (KR)]][[Category:Hyunkook Cho of Suwon-si (KR)]]

[[:Category:Kapil Sachdeva of Noida (IN)|Kapil Sachdeva of Noida (IN)]][[Category:Kapil Sachdeva of Noida (IN)]]

[[:Category:Pushpinder Goyal of Noida (IN)|Pushpinder Goyal of Noida (IN)]][[Category:Pushpinder Goyal of Noida (IN)]]

==METHOD OF TRACING KNOWLEDGE LEVEL OF USER CONSUMING CONTENT AND RECOMMENDING CONTENT BASED ON KNOWLEDGE LEVEL OF USER, AND COMPUTING DEVICE EXECUTING THE SAME - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240323464 titled 'METHOD OF TRACING KNOWLEDGE LEVEL OF USER CONSUMING CONTENT AND RECOMMENDING CONTENT BASED ON KNOWLEDGE LEVEL OF USER, AND COMPUTING DEVICE EXECUTING THE SAME

'''Simplified Explanation''': This patent application describes a method for tracing the knowledge level of a user by sensing their reaction to consuming content, determining their understanding of the content based on their reaction, inputting this information into a knowledge tracing model, and updating the user's knowledge level accordingly.

* Tracing knowledge level of a user based on their reaction to content consumption
* Determining user understanding of content
* Inputting information into a knowledge tracing model
* Updating user's knowledge level based on model output

'''Potential Applications''': 
This technology could be applied in educational settings to track student learning progress and tailor teaching methods accordingly. It could also be used in personalized content recommendations in digital platforms.

'''Problems Solved''': 
This technology addresses the challenge of accurately assessing a user's knowledge level and understanding of content in real-time, allowing for more personalized and effective learning experiences.

'''Benefits''': 
The benefits of this technology include improved learning outcomes, personalized content recommendations, and enhanced user engagement with digital platforms.

'''Commercial Applications''': 
Title: Personalized Learning and Content Recommendation Technology
This technology could be commercially used in educational software, e-learning platforms, and content recommendation systems to enhance user experience and learning outcomes.

'''Questions about Knowledge Tracing Technology''':
1. How can this technology improve personalized learning experiences?
   - This technology can enhance personalized learning by accurately tracking user knowledge levels and adapting content accordingly.
2. What are the potential applications of this technology beyond education?
   - This technology could also be used in personalized content recommendations in digital platforms to enhance user engagement.


==Original Abstract Submitted==

a method of tracing a knowledge level of a user, includes: sensing a reaction of the user consuming content; determining an understanding of the user with respect to the content based on the reaction of the user; inputting the understanding and information about the content into a knowledge tracing model; and updating the knowledge level of the user based on an output from the knowledge tracing model.



[[Category:H04N21/25]]
[[Category:H04N21/442]]
[[Category:CPC_H04N21/251]]