US 12,340,184 B2
Intelligent table suggestion and conversion for text
Abhijith Asok, Bellevue, WA (US); Courtney Sarah Cochrane, Cambridge, MA (US); Jenna Hong, Acton, MA (US); Yang He, Newton, MA (US); Lucas Anton Rosenblatt, Brooklyn, NY (US); Aleksandr Polyakov, Berkeley, CA (US); Natalie Ann Mionis, Cambridge, MA (US); Amit Dinesh Gupte, Bellevue, WA (US); Anish Yatin Pimpley, Bellevue, WA (US); Sean Gormley T. Kelley, Boston, MA (US); Yiquan Xu, Watertown, MA (US); Ransom Lloyd Richardson, Acton, MA (US); Michael Adam Scarpati, Wellesley, MA (US); Benjamin Gustav Wilde, Quincy, MA (US); and Jichen Yang, Fremont, CA (US)
Assigned to Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed by Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed on Nov. 11, 2021, as Appl. No. 17/524,646.
Prior Publication US 2023/0143568 A1, May 11, 2023
Int. Cl. G06F 17/00 (2019.01); G06F 40/103 (2020.01); G06F 40/58 (2020.01); G06N 20/00 (2019.01)
CPC G06F 40/58 (2020.01) [G06F 40/103 (2020.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. An apparatus, comprising:
a device including at least one memory having processor-executable code stored therein, and at least one processor that is adapted to execute the processor-executable code, wherein the processor-executable code includes processor-executable instructions that, in response to execution, enable the device to perform actions, including:
receiving input text;
determining whether the input text includes at least three rows;
based on determining that the input text includes at least three rows, determining a plurality of characteristics of the input text, wherein each characteristic of the plurality of characteristics is associated with a uniformity between the rows of the input text, and wherein the plurality of characteristics includes at least one characteristic that is associated with a delimiter count;
making a determination as to whether the input text is suitable for table conversion based on the plurality of characteristics; and
in response to determining that the input text is suitable for conversion to a table, using a machine-learning model to convert the input text into a table.