US 11,782,592 B2
Method and apparatus for managing display of readable data presented in a portion of a display
Arshiyan Alam, Patna (IN); Abhinav Pachauri, Kanpur (IN); Pankaj Gupta, Punjab (IN); Nitin Barthwal, Delhi (IN); and Ravindra Jain, Greater Noida (IN)
Assigned to Samsung Electronics Co., Ltd., Suwon-si (KR)
Appl. No. 17/617,477
Filed by Samsung Electronics Co., Ltd., Suwon-si (KR)
PCT Filed Jun. 18, 2020, PCT No. PCT/KR2020/007882
§ 371(c)(1), (2) Date Dec. 8, 2021,
PCT Pub. No. WO2020/256424, PCT Pub. Date Dec. 24, 2020.
Claims priority of application No. 201941024170 (IN), filed on Jun. 18, 2019.
Prior Publication US 2022/0236845 A1, Jul. 28, 2022
Int. Cl. G06F 3/0485 (2022.01); G06F 40/106 (2020.01); G06F 3/0481 (2022.01); G06N 5/022 (2023.01); G06F 3/04883 (2022.01)
CPC G06F 3/0485 (2013.01) [G06F 3/0481 (2013.01); G06F 40/106 (2020.01); G06N 5/022 (2013.01); G06F 3/04883 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A method for managing operations on data presented on a display of an electronic device, the method comprising:
detecting data presented on a display of the electronic device;
determining reading parameters associated with the data; and
performing, by the electronic device, a plurality of operations based on the reading parameters,
wherein the reading parameters comprise at least one of a complete screen reading time taken by a user to completely read the data presented on the display of the electronic device, a partial screen reading time taken by the user to read at least one portion of the data, a scroll distance per one scrolling action on the display, or a data reading time which is a time taken to completely read the data presented on the display, and
wherein the plurality of operations include displaying a graphic indication indicating a portion of the data to be scrolled out within a predetermined time,
wherein the determining of the reading parameters are performed based a plurality of machine learning (ML) regression models, and
wherein the plurality of ML regression models are trained by:
dividing a screen of the display of the electronic device into a plurality of blocks;
extracting features of the data for each of the plurality of blocks;
generating a first training dataset comprising an actual time taken to completely read the data presented on the display, the extracted features per each of the plurality of blocks, and a context of the data;
generating a second training dataset comprising an actual scroll distance, the extracted features per each of the plurality of blocks, and the context of the data;
training a first ML regression model from the plurality of ML regression models using the first training set to determine the complete screen reading time; and
training a second ML regression model from the plurality of ML regression models using the second training dataset to determine the scroll distance per one scrolling action.