View source for US Patent Application 18221288. PERSONALIZED ELECTRONIC DEVICE INFERRING USER INPUT, AND METHOD FOR CONTROLLING SAME simplified abstract

=PERSONALIZED ELECTRONIC DEVICE INFERRING USER INPUT, AND METHOD FOR CONTROLLING SAME=


==Organization Name==

[[Samsung Electronics Co., Ltd.]]


==Inventor(s)==

[[Jinyoung Hwang of Suwon-si (KR)]]

[[Dongchan Kim of Suwon-si (KR)]]

[[Dongnam Byun of Suwon-si (KR)]]

==PERSONALIZED ELECTRONIC DEVICE INFERRING USER INPUT, AND METHOD FOR CONTROLLING SAME - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18221288 titled 'PERSONALIZED ELECTRONIC DEVICE INFERRING USER INPUT, AND METHOD FOR CONTROLLING SAME

==Simplified Explanation==

This patent application describes an electronic device that uses artificial intelligence to perform operations based on user inputs. The device collects touch data from the user and compares it to pre-stored training data sets to identify the type of input. It then trains an artificial intelligence model based on the identified data set and performs the corresponding operation.

* Electronic device uses artificial intelligence to perform operations based on user inputs
* Collects touch data from the user
* Compares touch data to pre-stored training data sets
* Identifies a similar training data set
* Trains an artificial intelligence model based on the identified data set
* Identifies the type of user input based on the trained model
* Performs the operation corresponding to the identified input type


==Original Abstract Submitted==

Provided is an electronic device configured to perform an operation corresponding to a user input by using an artificial intelligence model, and a method performed by the electronic device, of performing the operation. The method comprises obtaining touch data related to a touch input of a user, identifying a first training data set similar to the touch data from a plurality of pre-stored training data sets, training an artificial intelligence model based on the first training data set, identifying a type of a user input that is input to the electronic device, based on the trained artificial intelligence model, and performing an operation corresponding to the identified type of the user input.